|Year : 2018 | Volume
| Issue : 3 | Page : 97-102
The abnormal iron homeostasis among Egyptian obese children and adolescents: relation to inflammation of obesity
Ehab K Emam1, Marwa H.A Hamed1, Dina A Fouad2, Reham O Abd-Allah3
1 Department of Paediatric, Clinical Nutrition Unit, Faculty of Medicine, Ain Shams University, Cairo, Egypt
2 Department of Clinical Pathology (Hematology), Faculty of Medicine, Ain Shams University, Cairo, Egypt
3 General Practioner in ER, New Cairo Hospital, Cairo, Egypt
|Date of Submission||11-Nov-2017|
|Date of Acceptance||02-Jan-2018|
|Date of Web Publication||3-Dec-2018|
Marwa H.A Hamed
Department of Pediatrics, Clinical Nutrition Unit, Faculty of Medicine, Ain Shams University, Cairo 1159
Source of Support: None, Conflict of Interest: None
Background Obesity is associated with low-grade inflammatory changes that increase Fe tissue storage and affect the level of circulating serum Fe, leading to tissue overload and decreased availability of Fe for hematopoiesis.
Objectives The objectives of this study were to determine the relation between the low iron state and the chronic inflammation found in obese children and to assess the role of inflammatory markers in the detection of iron status.
Design and setting This was a case–control study. This study was conducted in the outpatient and clinical nutrition clinics of Pediatric Hospital, Ain Shams University.
Patients and methods This was a case–control study conducted on 50 obese children and adolescents over 1 year. They were divided into two subgroups: iron deficient and noniron deficient patients. The study also included 20 normal weight children and adolescents as controls. All patients were subjected to the obesity sheet, anthropometric measurements, complete blood picture, measurement of iron profile and high-sensitivity C-reactive protein (hs-CRP).
Results There were significantly lower mean values of hemoglobin, serum iron, ferritin and transferrin saturation among obese than among nonobese children. The mean serum level of hs-CRP was significantly higher among obese children than controls, and, of the 50 obese patients, 62% had high levels. The mean serum level of hs-CRP among anemic obese patients was significantly higher than in the nonanemic obese group. The hs-CRP showed significant positive correlations with BMI and significant negative correlations with serum iron.
Conclusion The chronic inflammation changes of obesity lead to a low iron state. Thus, regular follow-up of obese children by measuring serum hs-CRP, hemoglobin, and iron profile is mandatory.
Keywords: high-sensitivity C-reactive protein, inflammation, iron, obesity
|How to cite this article:|
Emam EK, Hamed MH, Fouad DA, Abd-Allah RO. The abnormal iron homeostasis among Egyptian obese children and adolescents: relation to inflammation of obesity. Egypt J Haematol 2018;43:97-102
|How to cite this URL:|
Emam EK, Hamed MH, Fouad DA, Abd-Allah RO. The abnormal iron homeostasis among Egyptian obese children and adolescents: relation to inflammation of obesity. Egypt J Haematol [serial online] 2018 [cited 2019 Aug 23];43:97-102. Available from: http://www.ehj.eg.net/text.asp?2018/43/3/97/246780
| Introduction|| |
Obesity is a worldwide chronic public health problem . There is great evidence that the initiating events in obesity-induced inflammation start early in childhood and lead to elevated inflammatory markers such as high-sensitivity C-reactive protein (hs-CRP) ,.
It was found that obesity is associated with iron deficiency and iron profile abnormalities, which appear to be caused by several factors such as decreased intake, insufficient bioavailability, and deficient intestinal iron uptake as well as iron release from stores because of an overexpression of hepcidin ,.
Adiposity-related inflammation is associated with a reduction in the normal upregulation of iron absorption in iron-deficient obese individuals, and this adverse effect may be ameliorated by fat loss .
It is important to identify the probable cause of the iron deficiency in obese children because of increased susceptibility of this age group to the negative effects of iron deficiency .
| Aims|| |
The aims of this study were the evaluation of the relation between the low iron state and the chronic inflammation found in obese children and to assess the role of inflammatory markers in the detection of iron status.
| Patients and methods|| |
This is a case–control study conducted on 50 [34 male and 16 female obese children and adolescents (>95th BMI percentiles)] obese children and adolescents diagnosed according to the criteria of Baker et al. . They were recruited from outpatient and clinical nutrition clinics of Pediatric Hospital, Ain Shams University. Their ages ranged between 2 and 15 years with a mean age of 10.12±3.24 years.
We excluded from the study, patients with an identified risk for iron deficiency or red cell disorder as those with heavy menstruation, gastrointestinal bleeding, elevated levels of lead, chronic anemias such as thalassemia, sickle cell disease, sidroblastic or aplastic anemia, those on a vegan diet and patients with cancer or inflammatory disorders such as inflammatory bowel disease, autoimmune or collagen disorders, patients with secondary obesity or endocrinal disorders as well as patients who were receiving iron supplements, immunosuppressive medications or corticosteroids within the last year.
The included patients (group I) were divided according to their iron profile  into two subgroups: group Ia, which included 21 male participants and nine female participants who were iron deficient, and group Ib, which included 13 male participants and seven female participants who were noniron deficient patients.
The study also included 20 controls (group II) (13 male participants and seven female participants) who were children and adolescents with normal weight (15th <85th BMI percentiles). Their ages ranged between 2 and 15 years with a mean age of 9.88±3.44 years.
The sample size was calculated to provide 95% confidence and 80% power in statistical analysis.
The Ethical and Research Committee of the Council of Children Department, Ain Shams University, Egypt, approved this study proposal. Full description of what was required in the study was discussed with the parents of the participants, and consent was obtained before the evaluation.
| Methods|| |
The enrolled patients were subjected to the obesity sheet aiming to reveal the demographic data, obesity risk factors, demonstration of morbidities and comorbidities of obesity, body image, psychological problems and previous history of diet control.
Anthropometric measurements were performed to all involved children and adolescents using standardized equipments, and we followed the recommendations of the International Biological Programme . These measurements included weight (wt) in kilograms (kg), height (ht) in centimeter (cm), waist circumference (WC) in centimeter (cm), mid-upper arm circumference (MUC) in centimeter (cm) and triceps and subscapular skinfold thickness in millimeter (mm) using Harpenden skinfold caliper (England Baty International Victoria Road Burgess Hill West Sussex RHI5 9LR). BMI was calculated according to the following equation: BMI=weight (kg)/height (m2) .
Age-specific and sex-specific z scores for height, weight, and BMI were calculated by using year 2000 growth data from the National Center for Health Statistics, and Centers for Disease Control and Prevention. This was achieved through using the Window-based software Epi Info. Children were classified by BMI z score categories as normal weight (BMI z score >−2 SD<+1 SD), overweight (BMI z score ≥+1 SD<+2 SD), and obese (BMI z score≥+2 SD) .
A volume of 6 ml peripheral blood was collected from all participants using standard venipuncture techniques in two tubes. Of which 2 ml on EDTA was utilized for complete blood picture, and 4 ml serum was utilized for iron profile and hs-CRP. Hemolytic, lipemic, or turbid samples were excluded after centrifugation.
Hemoglobin concentration was measured using Coulter counter Max-M (Coulter Corporation, Florida, USA) to assess for anemia, with cut-off values based on the fifth percentile for a reference group .
Iron profile assessment
Serum levels of iron were measured by colorimetric reaction kits (supplied by Beckman Coulter, Brea, California, USA) on an automated analyzer (CX7, Synchron Clinical System; Beckman Coulter). Reference value in children for serum iron is 50–120 μg/dl.
Serum ferritin was assessed by IMMULITE/IMMULITE 1000 Ferritin analyzer (Siemens, Los Angeles, California, USA). Reference value in children for serum ferritin is greater than 10 ng/dl.
Total iron-binding capacity (TIBC) was measured by colorimetric kits produced by Spectrum Company (München, Germany). Reference value in children for TIBC is 250–400 μg/dl.
Transferrin saturation was calculated by using the following equation: saturation of Tf=(serum iron divided by TIBC)×100 .
The child was considered as iron deficient if serum iron was lower than 50 μg/dl, serum TIBC was higher than 400 μg/dl , serum ferritin was less than 10 ng/ml , or transferrin saturation was less than 16% .
Hs-CRP was used as a marker of inflammation. Serum levels of hs-CRP were measured using ELISA . The hs-CRP values were classified by American Heart Association standards for risk for cardiovascular disease as low (<1 mg/l), intermediate (1–3 mg/l), or high (>3 mg/l) .
The collected data were revised, coded, tabulated, and introduced into a PC using statistical package for the social sciences (SPSS Inc., Chicago, Illinois, USA) .
| Results|| |
The results of this work show that of the 50 obese patients, 27 (54%) had a family history of obesity, 15 (30%) had a habit of consuming fast food, 35 (70%) patients bought food from street vendors, 46 (92%) were heavy beverage consumers, 25 (50%) patients had their food while watching TV, 29 (58%) patients had negative nutritional behavior, 41 (82%) did not follow any diet previously, and 42 (84%) did not have physical exercise.
There were significantly lower mean values of hemoglobin level, serum iron, serum ferritin, and transferrin saturation and significantly higher mean serum TIBC among obese patients (P<0.001) ([Table 1]).
|Table 1 Comparison between obese and nonobese patents with regard to blood picture and iron profile|
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On comparing between anemic and nonanemic obese cases, we found that the percentages of patients belonging to the low socioeconomic class were significantly higher among anemic (76%) than nonanemic patients (10%) with P value of less than 0.05. Further, the percentages of negative feeding behavior and the absence of exercise practice were significantly higher among anemic (90 and 93.3%) than in nonanemic obese cases, with P value of less than 0.01 and 0.05, respectively. However, there were no significant differences as regards other personal and familial characteristics, other nutritional habits, previous diet, mineral intake, or anthropometric measurements.
The mean serum level of hs-CRP was significantly higher in the obese group than in the nonobese group with P value of less than 0.001 ([Table 2]).
Moreover, the mean serum level of hs-CRP among anemic obese patients (mean±SD, 8.35±2.97) was significantly higher than in the nonanemic obese group (3.16±1.89 with P<0.001] ([Table 3]).
|Table 3 Comparison between anemic and nonanemic obese cases as regards high-sensitivity C-reactive protein|
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The hs-CRP proved to have significant positive correlations with mean z scores of weight, BMI ([Figure 1]), and triceps skinfold and with TIBC and significant negative correlations with hemoglobin, serum iron ([Figure 2]), serum ferritin, and transferrin saturation ([Table 4]).
|Figure 1 Scattered diagram showing a positive correlation between high-sensitivity C-reactive protein and BMI. Hs-CRP, high-sensitivity C-reactive protein.|
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|Figure 2 Scattered diagram showing a negative correlation between high-sensitivity C-reactive protein and serum iron. Hs-CRP, high-sensitivity C-reactive protein.|
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|Table 4 Correlations between high-sensitivity C-reactive protein and anthropometric measurements, hemoglobin concentration, and serum levels of iron profile|
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The mean z scores of BMI showed significant negative correlations with serum iron, serum ferritin, and transferrin saturation and a significant positive correlation with TIBC. However, no significant correlation was found between mean z scores of BMI and hemoglobin levels ([Table 5]).
| Discussion|| |
In the present study, it was evident that the mean serum level of hs-CRP was significantly higher in the obese than in the nonobese group, and the majority of the studied obese children had levels of hs-CRP that indicated high or intermediate risk for cardiovascular disease. This result is in agreement with the study published by Pearson et al. , whereas the majority of the studied nonobese controls had levels of hs-CRP that indicated low or intermediate risk for cardiovascular diseases. Further, we proved a positive correlation between BMI and hs-CRP among obese patients. These results are in accordance with the study of Baker et al.  who showed that an elevated BMI in childhood was associated with significantly increased risk of both fatal and nonfatal coronary heart disease later in life. Further, the study of Diaz et al.  confirmed that obese children had elevated levels of hs-CRP and that the more obese a child was, the more the systemic inflammation is the child was exposed to. This is explained by the fact that excess fat deposited in visceral organs leads to low-grade chronic inflammation that causes insulin resistance and the associated comorbidities of metabolic syndrome Halberg et al. .
In this study, obese cases recorded significantly lower values of hemoglobin, serum levels of iron and ferritin, transferrin saturation and significantly higher values of TIBC compared with nonobese controls. Further, BMI revealed significant negative correlations with serum levels of iron and ferritin and with transferrin saturation and a significant positive correlation with TIBC. This is in agreement with the studies of Cepeda-Lopez et al.  and Moschonis et al.  whose results suggested that increasing BMI was associated with lower serum levels of iron and transferrin saturation. Moreover, Azab et al. , Abd-El Wahed et al. , and Shekarriz and Vaziri , found that serum levels of iron and ferritin were significantly lower among obese children compared with nonobese Egyptian children. Moreover, in a cross-sectional study in Chilean women, obese women had lower fractional iron absorption than did overweight and normal weight women (P<0.05) .
In contrast to our study, Tussing-Humphreys et al.  and Cheng et al.  found hemoglobin levels to be higher in obese individuals, and Tussing-Humphreys et al.  found the ferritin levels to be higher in the obese children, even before iron supplementation. Moreover, Baumgartner et al.  stated that, although iron deficiency was found in overweight and obese individuals, ferritin was usually normal or increased. Ausk and Ioannou  hypothesized that serum ferritin (acute-phase reactant) may increase in obesity because of inflammation; moreover, it would be expected to cause a decrease in serum iron, a well-documented response to infection or inflammation. Therefore, their findings suggested that obesity was associated with changes in serum iron markers that are typical of chronic inflammation, but was not actually associated with anemia of inflammation.
The high rate of iron deficiency among obese children is explained by several mechanisms, such as consumption of high calories, poor dietary iron intake, and sedentary life style, resulting in decreased breakdown of myoglobin and increased iron requirements for increased red cell mass . A more likely explanation is that chronic adiposity-related inflammation causes decreases in intestinal iron absorption and/or increases reticuloendothelial iron sequestration, which is caused by increased hepcidin concentrations . Hepcidin is produced primarily in the liver but is expressed in adipose tissue as well . Interleukin-6 increases its expression, which is higher in obese children. In addition, there are data to suggest that the adipose-derived hormone, leptin, increase hepcidin expression . Hepcidin is an important regulator of Fe homeostasis, inhibiting Fe absorption at the enterocyte and sequestering Fe at the macrophage, which could lead to decreased Fe stores and hypoferremia and anemia of chronic disease observed in obesity . It was suggested that inflammation-induced hepcidin was likely causing a decrease in dietary iron absorption, by diminishing the expression of ferroprotein (Fpn) located on the basolateral membrane of intestinal enterocytes, thus impairing dietary repletion efforts .
In our study, the mean serum level of hs-CRP among anemic obese patients was significantly higher than in the nonanemic obese group, and, of the 30 anemic obese patients, 29 (98%) had high levels and only one (2%) had intermediate levels of hs-CRP. Further, we found negative correlations between hs-CRP levels and the serum levels of iron, ferritin and transferrin saturation. This is in accordance with Yanoff et al.  whose data supported that it is the inflammation of obesity that negatively influences iron homeostasis and with Richardson et al.  whose study showed negative associations of hs-CRP with serum iron, transferrin saturation, and hemoglobin. Moreover, Anty et al.  reported on obese adult women who had bariatric surgery, and found that the postoperative decrease in BMI was associated with decrease in CRP levels, with an associated improvement in markers of iron status, further suggesting that it is obesity that leads to inflammation, which in turn contributes to abnormal measures of iron homeostasis.
Finally, we concluded that the chronic inflammation of obesity disturbs the basic iron homeostasis in obese children and adolescents and leads to a low iron profile among obese people. Thus, regular follow-up of obese children and adolescents by measuring serum hs-CRP, hemoglobin, serum iron, ferritin, transferrin concentration, and TIBC is mandatory to offer proper treatment when needed.
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Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]