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Relationship of serum irisin levels, physical activity, and metabolic syndrome biomarkers in obese individuals with low-calorie intake and non-obese individuals with high-calorie intake

Journal of Health, Population and Nutrition volume 44, Article number: 2 (2025) Cite this article

Abstract

Background

Despite all the advances in our knowledge regarding obesity, our understanding of its etiology is still far from complete. This study aimed to evaluate the association of serum irisin levels with physical activity and some of the metabolic syndrome-related biomarkers among obese people with low-calorie intake and non-obese people with high-calorie intake.

Methods

Obese and non-obese healthy individuals with respectively low and high-calorie intakes were recruited. Irisin and other biomarkers were measured using standard biochemical methods. Participants’ physical activity was evaluated by administering the International Physical Activity Questionnaire (IPAQ). To analyze the body composition of the participants, a standard body composition device (ioi 353) was applied. Logistic regression was used to calculate the odds ratio (OR) and to examine the effect of confounders such as age, sex, genetics, and activity.

Results

Data from the seventy-seven participants were included in the final analysis. The mean age of the participants in the obese and non-obese groups was 38.33 ± 14.88 and 30.24 ± 13.37 years, respectively. Participants in the obese group had lower physical activity compared to the non-obese group (3395.38 ± 2801 MET-min/week vs. 6015.18 ± 3178 MET-min/week; p < 0.001). The Irisin concentration in the obese and non-obese groups was 7.84 ± 2.49 ng/ml and 8.06 ± 1.89 ng/ml, respectively, which wasn’t significantly different (p = 0.66). We observed a noteworthy and favorable association between irisin concentration and total body water (TBW), lean body mass (LBM), and soft lean mass (SLM) in the non-obese group.

Conclusions

These data indicated that although obese participants were relatively inactive compared to non-obese individuals, circulating irisin level wasn’t significantly different between the two groups.

Highlights

No irisin difference between obese and non-obese groups.

Physical activity unrelated to irisin levels.

Positive irisin correlation with lean mass in non-obese group.

Triglycerides and cholesterol lower in non-obese group.

Irisin linked to TSH and glucose levels in obesity.

Background

The occurrence of chronic diseases related to obesity has significantly increased in most countries [1,2,3]. Reputable institutions define obesity as an imbalance between calories consumed and calories expended, which is widely accepted as the primary cause of overweight and obesity [4]. Most preventive and treatment approaches for obesity are based on reducing caloric intake, increasing caloric expenditure, or a combination of both. However, the energy balance or imbalance approach may not be entirely accurate, and it can be argued that considering obesity solely in terms of energy balance may be one of the reasons for the failure of public health approaches to reverse the obesity epidemic [5,6,7]. One of the contradictions in the concept of energy balance is related to obese individuals who do not lose weight despite consuming low calories, or lean individuals who do not gain weight despite consuming higher calories [8].

Exercise has emerged as a key factor in weight management and metabolic health.Myokines, including irisin, have been implicated in the beneficial effects of physical activity [9,10,11]. Irisin, a hormone produced by fibronectin type III domain containing 5 (FNDC5) in skeletal muscle, is believed to be a myokine produced during exercise that promotes the transformation of white adipose cells into brown-fat-like cells [12]. This transformation can significantly affect metabolism and energy homeostasis [12, 13].

One possible explanation for the question of why some thin individuals can consume a high number of calories without gaining weight, while some overweight individuals struggle to lose weight despite consuming fewer calories, is that the former group may have more brown adipose tissue (BAT) and engage in more physical activity than the latter group [14]. However, directly measuring the amount of BAT in the body is difficult, and indirect methods such as measuring serum levels of irisin may be a suitable alternative.

The regulation of food intake and body weight is controlled by a complex system of peptide and protein factors, as noted in a study by Suzuki et al. in 2012 [15]. Previous research has examined the relationship between serum irisin levels and obesity or food intake, but the results have been mixed. In a meta-analysis study, Jia et al. found that the concentration of this hormone was higher in individuals with obesity or overweight compared to healthy controls [16]. However, no previous study has investigated the levels of this peptide in obese individuals with limited calorie intake or lean individuals with high-calorie intake. This study aims to investigate the relationship between serum irisin levels, metabolic parameters, and physical activity in two distinct groups: (1) obese individuals who maintain a low caloric intake and (2) lean individuals who consume a high caloric intake.

Materials and methods

Design of the research study and gathering of samples

The study followed the guidelines outlined in the Declaration of Helsinki [17], and all procedures that involved human subjects or patients were approved by the Ethics Committee of Zanjan University of Medical Sciences (Ethics Code: IR.ZUMS.REC.1400.235) and the Ethics Committee of the National Institute for Medical Research Development (Ethics Code: IR.NIMAD.REC.l397.539). All participants provided written and informed consent, and this was obtained from all subjects/patients. The study involved two groups of individuals who were classified based on their calorie intake. The first group consisted of obese individuals with a low-calorie intake, while the second group comprised of non-obese individuals with a high-calorie intake. The research was conducted at the specialized nutrition clinic of Zanjan University of Medical Sciences in Zanjan, Iran, from June 2020 to September 2021.

The study data of Hou et al. was used to calculate the sample size for this study [18] on irisin and using the following formula.

$$\:n=\frac{{\left({Z}_{1-\frac{\alpha\:}{2}}+{Z}_{1-\beta\:}\right)}^{2}\times\:\left({s}_{1}^{2}+{s}_{2}^{2}\right)}{{\left({\mu\:}_{1}-{\mu\:}_{2}\right)}^{2}}$$

Z 1−α/2 = 1.96, Z1−β= 0.84, µ1 = 194.8, S1 = 19.9, µ2 = 180.5, S2 = 22.4.

To account for potential sample loss, the required sample size for each group was calculated as 34 people, which was adjusted to 42 people for each group. The participants in the case group were selected from volunteers who were referred to the nutrition clinic of Zanjan University of Medical Sciences and met specific criteria: they were obese individuals (BMI > 30) who were known among their family and friends for eating very little, and their estimated calorie intake, based on a three-day 24-hour food recall, was less than 50% of the required calories based on their dietary report in perevious year (calculated using the Mifflin St. Jeor equation) [19].

We chose participants for the control group based on two criteria: their BMI had to be less than 25 kg/m2, and they had to be known for eating more than their peers, with an estimated caloric intake of more than 50% of the required calories based on their dietary report in perevious year. The study excluded individuals with certain conditions, such as a history of diseases that could affect weight (e.g., diabetes, thyroid disorders, cancer, polycystic ovary syndrome), as well as those taking medications that could affect weight (e.g., corticosteroids), or those who had followed weight-loss or gain diets in the past year.

Calories estimation

In order to determine the caloric intake of the study participants, researchers conducted a three-day 24-hour food recall [20], which included at least one weekday and one weekend day. The information obtained from the recall was then evaluated using Nutritionist IV software (N Squared Computing, California, USA) to calculate the average caloric intake of each individual. The average calories obtained from the three-day recall questionnaire were then compared to the calories obtained through the Mifflin St. Jeor equation [21], which is based on the following formula:

Males: kcal/day = 10 (weight) + 6.25 (height) − 5 (age) + 5.

Females: kcal/ day = 10 (weight) + 6.25 (height) − 5 (age) – 161.

As previously stated, individuals with obesity were eligible to enter the case group if their average calorie intake was less than 50% of the calories estimated by the Mifflin St. Jeor equation [21]. Conversely, non-obese individuals were eligible to enter the control group if their average calorie intake was more than 50% of the estimated calories.

Anthropometric and physical activity assessment

The participants’ height and weight were recorded while wearing light clothing and without shoes, with an accuracy of 1 cm and 0.1 kg, respectively. The BMI was determined by dividing the body weight (in kilograms) by the square of the height (m2). For physical activity assessment, we applied the IPAQ [22]. Body composition was analyzed by a standard body composition device (ioi 353).

Biochemical measurements

All participants were required to fast for 10 to 12 h before 10 ccs of blood were drawn for biochemical tests. The blood samples were then spun at 4000 revolutions per minute for 10 min at room temperature to separate the serum, which was stored in separate portions at a temperature of -80° Celsius until ready for biochemical analysis. The evaluation of serum irisin levels was conducted using the enzyme-linked immunosorbent assay (ELISA) kit (Zellbio, Cat.No: ZB-13253 C-H9648), with an intra-assay CV for irisin kit of < 10% and inter-assay precision CV (%) = SD/mean x 100, with inter-assay CV < 12%. To measure serum TSH, ELISA kits (Pishtazteb Diagnostics, Iran) were used, while serum glucose, triglycerides, total cholesterol, ALT, and AST were measured using photometric assays (Parsazmoun, Iran).

Statistical analysis

The SPSS software (SPSS Inc., Chicago, IL) version 18 was used for statistical analyses. Quantitative data were reported using mean and standard deviation, while qualitative data were reported using frequency expressed as a percentage. The Mann-Whitney U test was utilized to compare the studied variables in the two groups due to abnormal data distribution. Logistic regression was used to calculate the odds ratio (OR) and examine the effect of confounders such as age, sex, genetics, and activity, which were also entered into the model. A binary logistic regression model was used to examine the association between serum irisin levels and the likelihood of being classified as obese. Independent variables included in the model were age, sex, physical activity (MET-min/week), TBW, LBM, SLM, FBS, TG, TC, and TSH. Variables were selected based on their potential confounding effect and biological plausibility A p-value less than 0.05 was considered significant in all analyses.

Results

Study population

After applying the inclusion and exclusion criteria, a total of 36 individuals in the obese group and 41 individuals in the non-obese group were included in the final analysis. As indicated in Table 1, the mean age of the obese group participants was 38.33 ± 14.88 years, which was significantly different from the mean age of the non-obese group participants (30.24 ± 13.37 years) with a P-value of 0.014. In the obese group, 80% of the participants were female, while in the non-obese group, 63% of the participants were female, with a p-value of 0.097. Additionally, the mean weight of the obese group participants was 92.96 ± 12.86 kg, which was significantly different from the mean weight of the non-obese group participants (56.17 ± 8.87 kg) with a P-value of less than 0.001. Furthermore, the BMI, waist circumference, and hip circumference of the two groups were significantly different with a p-value of less than 0.001. The average energy intake of the obese group participants was 1161.35 ± 357.61 kcal/day, which was significantly different from the average energy intake of the non-obese group participants (3129.90 ± 1002.01 kcal/day) with a P-value of less than 0.001.

Table 1 Participants’ characteristics among the participants in case and control groups
Full size table

Comparison of physical activity and body composition in obese and non-obese groups

According to Table 2, the physical activity level of participants in the obese group was lower than that of the non-obese group (3395.38 ± 2801 MET-min/week compared to 6015.18 ± 3178 MET-min/week, with a P-value of less than 0.001). Additionally, it has been reported that individuals in the obese group had higher percentages of lean body mass (LBM) (54.18 ± 8.77% compared to 45.12 ± 7.72%, with a P-value of less than 0.001), body fat percent (PBF) (38.91 ± 5.33% compared to 21.12 ± 7.40%, with a P-value of less than 0.001), soft lean mass (SLM) (49.18 ± 8.06 compared to 41.80 ± 7.27, with a P-value of less than 0.001), and total body water (TBW) (39.00 ± 6.32 kg compared to 32.48 ± 5.55 kg, with a P-value of less than 0.001).

Table 2 Comparison of participants in the case and control groups in relation to anthropometric indicators and physical activity level
Full size table

Comparison of biochemical variables in obese and non-obese groups

Table 3 summarizes the results of the comparison of biochemical variables between obese and non-obese individuals. The irisin concentration in the obese group was 7.84 ± 2.49 ng/ml, while in the non-obese group, it was 8.06 ± 1.89 ng/ml. However, there was no significant difference between the two groups (P = 0.66). Although all participants had normal lipid profiles, individuals in the obese group had significantly higher levels of TG (137.11 ± 60.18 mg/dl compared to 83.5 ± 43.19 mg/dl, with a P-value of less than 0.001) and cholesterol (163.02 ± 36.44 mg/dl compared to 135.65 ± 30.82 mg/dl, with a P-value of 0.001). There were no significant differences between the two groups in terms of TSH, glucose, creatinine, ALT, and AST (with P-values greater than 0.05).

Table 3 Comparison of biochemical factors in case and control groups
Full size table

Association between irisin levels with risk of obesity and other biochemical parameters

The logistic regression test results indicated that there was no significant correlation between irisin concentration and obesity risk in both the crude and fully adjusted models (OR = 1.32, CI: 0.839, 2.10; P = 324). Table 4 demonstrated the relationship between irisin levels and metabolic parameters. The non-obese group showed a positive correlation between irisin levels and TBW (r = 0.439, P = 0.007), SLM (r = 0.449, P = 0.006), and LBM (r = 0.412, P = 0.005), while the obese group did not. In the obese group, there was an inverse correlation between irisin levels and glucose concentration (r=-0.354, P = 0.037) and ALT (r=-0.343, P = 0.043), and a positive correlation with TSH (r = 0.415, P = 0.013). Additionally, a favorable correlation was observed between irisin levels and TSH (r = 0.775, P = 0.045) in the non-obese group. The association between TBW, SLM, LBM, TSH, and age with irisin was significant (P < 0.001) in the between-group analysis.

Table 4 Association of biochemical and anthropometrical factors with the level of Irisin
Full size table

Discussion

The primary aim of this study was to investigate the relationship between irisin levels during rest and both anthropometric and metabolic factors. Additionally, the study aimed to compare the serum levels of this hormone between obese and non-obese participants. The study results indicated that there were no significant differences in irisin concentration between the two groups. However, the obese group had lower physical activity levels but higher levels of TG and cholesterol compared to the non-obese group. The study also found a significant correlation between irisin levels and certain anthropometric variables, glucose, TSH, and ALT concentration. Morever, we found that there was a significant difference between two group in term of height, but it has been mentioned that the reason for the higher height in the non-obese group may be the low percentage of women.

Irisin is a type of adipomyokine that can create heat in both muscle and adipose tissue, leading to an increase in energy usage through the process of white adipose tissue browning. In certain animal models, FNDC5/irisin is mainly released by adipocytes located in the subcutaneous adipose tissue (SAT), with a smaller amount being secreted by adipocytes in the visceral adipose tissue (VAT) [23]. However, it has been reported that in humans, the expression of FNDC5 is significantly lower in white adipose tissue (WAT) compared to muscle, and that WAT can affect the overall levels of irisin in the body [24,25,26].

Several studies have been conducted on humans to investigate the potential connections between levels of circulating irisin and obesity. Certain cross-sectional studies among these have indicated a positive correlation between irisin and obesity [24, 27], while others reported conflicting results [28,29,30]. The current study did not reveal any noteworthy variations in irisin levels between the two groups. Consistent with our results, Wu et al. conducted a study to explore the connection between irisin concentration and components of metabolic syndrome, and found that the serum irisin levels in men and women across the normal, overweight, and obese groups were not significantly dissimilar [31]. Additionally, a meta-analysis study revealed that the levels of irisin are greater in obese individuals than in healthy controls. Nevertheless, it is noteworthy to mention that in this meta-analysis, only studies conducted on African populations showed higher irisin levels in obese individuals compared to healthy controls, while in other populations, consistent with our findings, irisin levels were lower in obese individuals compared to the control group [16]. The findings suggest that particular hormone levels, like irisin, can be affected by genetic variations or maybe it has been related to this fact that the obese individuals in our study had very low energy intake.

In the current study, we were exploring a hypothesis that individuals who are not obese but consume a high amount of calories may exhibit elevated levels of serum irisin. Irisin can enhance the presence of uncoupling protein 1 (UCP1) in the mitochondrial membrane. This, in turn, helps to transfer protons back to the mitochondrial matrix without producing ATP at the same time [32, 33]. This process stimulates cellular respiration and increases energy, allowing for the pumping of protons and the recovery of the proton gradient across the inner mitochondrial membrane [34]. By stimulating the metabolic activity of fat tissue, Irisin causes an increase in uncoupling protein 1 (UCP1) in the mitochondrial membrane. This increase in UCP1 leads to greater oxygen consumption. However, despite this increase in metabolic activity, most of the energy produced is dissipated as heat [35, 36]. It has been reported that administering irisin to animal models resulted in a noteworthy enhancement in the activity of skeletal muscle cells and an increase in mitochondrial oxygen consumption [37]. Additionally, irisin promotes the functions of genes that elevate fat and muscle metabolism [36]. Although we had hypothesized that there would be a correlation between irisin concentration and physical activity, our results did not confirm this. It is possible that further controlled studies may be necessary to either confirm or reject our hypothesis. Our study did reveal a significant difference in physical activity between the two groups, but we did not observe any significant correlation between irisin concentration and physical activity. This finding is consistent with the results of Hofmann et al., who also reported no significant correlation between irisin levels and physical activity in patients with anorexia nervosa [38]. Also, Palermo et al. showed a non-significant correlation with daily physical activity [39].

The current study found that among non-obese participants, there was a significant positive correlation between irisin levels and TBW, LBM, and SLM. However, the relationship between irisin levels and both muscle mass and fat-free mass (FFM) is still unclear and contradictory. reported no significant association between irisin levels and FFM [40], while Löffler et al. reported an inverse correlation between irisin and FFM in German children and adolescents [41]. In contrast, some other studies have reported a positive correlation between irisin and FFM [42, 43].

The study found no significant difference in fasting blood sugar (FBS) concentration between the two groups. However, studies investigating the relationship between irisin and metabolic syndrome-related factors have produced conflicting results. For instance, in a cross-sectional study, Sahin-Efe et al. reported significant differences in irisin levels between non-obese individuals with normal glucose tolerance and obese individuals with impaired fasting glucose or diabetes [44]. According to some animal studies, irisin has been found to enhance insulin function. Additionally, other animal studies have reported a significant correlation between reduced irisin secretion and the occurrence of insulin resistance [45, 46]. In contrast, a cross-sectional study conducted by Sesti et al. revealed a negative association between the level of irisin in the bloodstream and insulin sensitivity [47]. Similar results were also shown in other studies [48, 49]. The reason why irisin lowers glucose levels may be attributed to both an increase in glucose absorption and an increase in energy expenditure [50,51,52,53]. Our study was conducted on healthy individuals with normal blood sugar levels, which is one reason why our findings differ from those of other studies. Previous research has proposed that patients with type 2 diabetes or pre-diabetes have lower levels of the transcriptional co-activator PPAR-γ co-activator-1 α (PGC1α) in their skeletal muscles, which is a molecule that is upstream of irisin. As a result, their circulating irisin levels may be lower than those of healthy obese individuals [13, 54].

The current study found that the levels of triglycerides and total cholesterol were significantly higher in the obese group compared to the non-obese group. However, there was no significant correlation between the concentration of irisin and the levels of triglycerides and total cholesterol. These findings are consistent with a cross-sectional study conducted by Mehrabian et al. among participants with normal weight obesity (NOW), which also found no significant correlation between irisin levels and lipid profile or glycemia [55,56,57,58]. Furthermore, Sanchis-Gomer et al. demonstrated that there was no significant correlation between the concentration of irisin and TC, TG, and LDL [59]. In contrast, the study conducted by Wen et al. revealed a significant correlation between the levels of irisin and TG, LDL, and TC in individuals without diabetes [60]. Some researchers have suggested that the association between irisin concentrations and lipid profile may be due to its effect on leptin concentration [55, 61].

This study was the first to examine the relationship between irisin levels, physical activity, and metabolic variables in obese individuals with low-calorie intake and non-obese individuals with high-calorie intake. Despite the study’s strengths, there were limitations that must be considered when interpreting the results. Firstly, the cross-sectional design of the study prevents us from making any conclusions about the role of irisin in the development of glycemic or lipid profile disturbances. Secondly, although the participants were carefully selected and their dietary intake was verified using both three-day 24-hour recall and FFQ methods, the selection process relied on self-reported data and may be subject to bias.

Conclusion

Our study did not find significant differences in irisin levels between obese individuals with low-calorie intake and non-obese individuals with high-calorie intake. However, given the conflicting evidence in the literature, further research with larger sample sizes and more diverse populations is recommended to clarify the role of irisin in obesity and metabolic health. Longitudinal studies could also help in understanding the causal relationships between irisin levels, physical activity, and metabolic outcomes. Although our study did not find a direct association between irisin levels and glycemic or lipid profiles, healthcare providers should consider the complex and multifactorial nature of obesity. Treatment and prevention strategies should continue to focus on comprehensive lifestyle interventions, including diet and physical activity, while recognizing that individual responses may vary. Further research is needed to fully understand why some individuals with high-calorie intake do not gain weight while others with very low calorie intake become obese.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

BMI:

Body Mass Index

IPAQ:

International Physical Activity Questionnaire

OR:

Odds Ratio

TBW:

Total Body Water

LBM:

Lean Body Mass

SLM:

Soft Lean Mass

FNDC5:

Fibronectin Type III Domain Containing 5

PPAR-γ:

Peroxisome Proliferator-Activated ReceptorGamma

PGC-1α:

Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1 Alpha

BAT:

Brown Adipose Tissue

TSH:

Thyroid Stimulating Hormone

ALT:

Alanine Aminotransferase

AST:

Aspartate Aminotransferase

ELISA:

Enzyme-Linked Immunosorbent Assay

CV:

Coefficient of Variation

WAT:

White Adipose Tissue

UCP1:

Uncoupling Protein 1

FFM:

Fat-Free Mass

FBS:

Fasting Blood Sugar

TC:

Total Cholesterol

TG:

Triglycerides

LDL:

Low-Density Lipoprotein

SAT:

Subcutaneous Adipose Tissue

VAT:

Visceral Adipose Tissue

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Acknowledgements

The author thanks the participants and their families who took part to the study.

Funding

This research project was supported by National Institute for Medical Research Development (NIMAD) Grant No.972375.

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Authors and Affiliations

  1. Social Determinants of Health Research Center, Health and Metabolic Diseases Research Institute , Zanjan University of Medical Sciences, Zanjan, Iran

    Jalal Hejazi

  2. Metabolic Diseases Research Center, Health and Metabolic Research Institute , Zanjan University of Medical Science , Zanjan, Iran

    Bijan Ghobadian

  3. Zanjan Health and Treatment Center, Health Deputy, Zanjan University of Medical Sciences, Zanjan, Iran

    Nasrin Ghasemi

  4. Department of Nutrition, School of Public Health, Zanjan University of Medical Sciences, Zanjan, Iran

    Jalal Hejazi, Hossein Sadeh, Nasim Abedimanesh & Mehran Rahimlou

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  1. Jalal Hejazi
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  4. Hossein Sadeh
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  5. Nasim Abedimanesh
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  6. Mehran Rahimlou
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Contributions

JH conceived the study, JH, BGh, HS, NGh and NA collected and analysed the data, MR interpreted the statistical analyses and wrote the first draft of the manuscript. JH contributed to the manuscript writing. All of the authors critically revised the manuscript. Theauthor(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Bijan Ghobadian or Mehran Rahimlou.

Ethics declarations

Ethics approval and consent to participate

The study was conducted in compliance with the Declaration of Helsinki and the protocol of the research was approved by the Ethics Committee of Zanjan University of Medical Sciences (Ethics Code: IR.ZUMS.REC.1400.235) and the Ethics Committee of the National Institute for Medical Research Development (Ethics Code: IR.NIMAD.REC.l397.539). Before the data collection, participants were explained the aims and methodology of the study and then were asked to sign a written informed consent letter.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Hejazi, J., Ghobadian, B., Ghasemi, N. et al. Relationship of serum irisin levels, physical activity, and metabolic syndrome biomarkers in obese individuals with low-calorie intake and non-obese individuals with high-calorie intake. J Health Popul Nutr 44, 2 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41043-024-00730-0

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Keywords

Journal of Health, Population and Nutrition

ISSN: 2072-1315

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