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Relationship Between being Overweight and Iron Deficiency in Adolescents
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Pediatrics and Neonatology (2015) xx, 1e7
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ORIGINAL ARTICLE
Relationship Between being Overweight and Iron Deficiency in Adolescents Ya-Fang Huang a, Teck-Siang Tok b, Chin-Li Lu c, Hsing-Ching Ko d, Min-Yu Chen d,*, Solomon Chih-Cheng Chen d,e,* a
Department of Clinical Laboratory, Pingtung Christian Hospital, Pingtung City, Taiwan Department of Pediatrics, Pingtung Christian Hospital, Pingtung City, Taiwan c Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan d Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan e School of Medicine, Taipei Medical University, Taipei City, Taiwan b
Received Jun 24, 2014; received in revised form Dec 10, 2014; accepted Feb 13, 2015
Available online - - -
Key Words body mass index; ferritin; obese; serum iron
Objective: Being overweight has been considered to be a risk factor of iron deficiency (ID). The objective of this study was to examine the relationship between being overweight and body iron status among Taiwanese adolescents. Methods: A total of 2099 adolescents (1327 female) aged 12e19 years from four middle schools and one college in southern Taiwan participated in this study. Data on sex, age, body weight, height, hemoglobin concentration, plasma ferritin (PF), and serum iron (SI) levels were collected. According to the age- and sex-specific body mass index (BMI) percentiles, the participants were divided into four weight groups: underweight (<5th percentile), normal weight (5e84th percentile), overweight (85e94th percentile), and obese (95th percentile). A multivariate logistic regression model was used to estimate the odds ratio (OR) and the 95% confidence interval (CI) for each factor. Results: The correlation coefficients of linear regression were positive for BMIehemoglobin and BMIePF, but negative for BMIeSI. Compared with the normal-weight group, the obese group had a lower risk of PF level <15 mg/L with an OR (95% CI) of 0.51 (0.30e0.87) but a higher risk of SI <60 mg/dL with an OR (95% CI) of 1.78 (1.34e2.37). The percentages of low PF declined as BMI increased, but the percentages of low SI rose, from underweight to obesity groups.
* Corresponding authors. Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, 539 Zhongxiao Road, East District, Chia-Yi City, 60002, Taiwan. E-mail addresses: [email protected] (M.-Y. Chen), [email protected] (S.C.-C. Chen). http://dx.doi.org/10.1016/j.pedneo.2015.02.003 1875-9572/Copyright ª 2015, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved.
Please cite this article in press as: Huang Y-F, et al., Relationship Between being Overweight and Iron Deficiency in Adolescents, Pediatrics and Neonatology (2015), http://dx.doi.org/10.1016/j.pedneo.2015.02.003
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Y.-F. Huang et al Conclusion: The relationship between being overweight and depleted iron store depends on which indicator is used to define the iron deficiency. Being overweight or obese would not be a risk factor of ID in adolescents, if ID were defined by PF rather than SI level. Copyright ª 2015, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved.
1. Introduction
2. Methods
Iron deficiency (ID) may be the most common form of nutritional deficiency worldwide and it is a significant public health problem in both developed and undeveloped countries.1 In a nationally representative cross-sectional health study in the USA, the prevalence of ID was 9e11% for adolescent girls and women of childbearing age, corresponding to approximately 8 million women with ID.2 One previous national study in Taiwan showed that the prevalence of ID was 2e6% in adolescent males and 9e10% in adolescent females.3 ID may cause adverse effects, including reduced work capacity,4 delayed mental and physical development in children,5 lower cognitive or behavioral function,6,7 and impaired sensorimotor function.8 Since ID is an important public health issue, examining its determinants is important to public health research. Several predisposing factors have been mentioned in the literature, such as female sex, parasite infestation,9 and Helicobacter pylori infection.10 Some previous studies have suggested being overweight as a risk factor for ID.11e15 However, that being overweight may be a risk for ID is contrary to our general understanding, because ID is a micronutrient deficiency that usually occurs in the context of poor nutritional status. For example, the prevalence of ID is often higher in developing countries and it is also associated with lower socioeconomic status.1,16e19 One study in Indonesia found that thinner adolescents have a five-fold higher risk of suffering from ID anemia compared with nonthin adolescents.18 Another study in the USA found that children in households with inadequate food had an almost three-fold higher risk of ID than children in households with adequate food.19 Moreover, the causal mechanism of being overweight for ID still needs further study for clarification. One challenge to study the risk factor of ID is the diversity of ID diagnosis, for there are many tests but no consensus. Many indicators, such as plasma ferritin (PF), serum iron (SI), soluble transferrin receptor, zinc protoporphyrin, and mean corpuscular volume, have been used to diagnose ID through a single test or a combination of several tests.20e25 Combining several tests to diagnose ID may be appropriate in academic study, but this is not cost efficient for clinical practice or public health intervention. In practice, SI and PF are the two most frequently used single tests. However, their relationship with being overweight has not been well studied or compared. Thus, the objectives of this study were to examine the relationship between being overweight and body iron status in Taiwanese adolescents by comparing the two tests of SI and PF.
2.1. Ethics statement The Ethics Review Board of Pingtung Christian Hospital approved the protocol and informed consent prior to the commencement of this study. All participants or their parents provided written informed consent. All data were collected for statistical analysis only, and no personal identification was revealed or compromised.
2.2. Study population This study was based on routine health checkups that were given to adolescents when they entered school. A total of 2099 adolescents (1327 girls) from one junior high school (786 students, age 12e13 years), three senior high schools (973 students, aged 15e16 years), and one college (340 students, age 18e19 years) in Pingtung County in southern Taiwan participated in this survey in September 2010.
2.3. Laboratory data and definitions The physical examination and blood sampling were performed after an overnight fast. Bodyweight, height, blood hemoglobin, SI, and PF levels were measured. Venous blood was taken for biochemical analyses, which were performed at the certified clinical laboratory of Pingtung Christian Hospital using a Beckman Coulter LX-20 autoanalyzer (Beckman Coulter, Brea, CA, USA). All technicians were blind to the demographic data and body mass index (BMI) of the participants. We followed the previous studies and World Health Organization recommendations to define anemia as a hemoglobin concentration under 13 g/dL in males or 12 g/dL in females.25,26 Depleted iron store was defined as either a PF level <15 mg/L25,27 or SI level <60 mg/ dL.14,28 According to sex- and age-specific BMI criteria,29 we classified all of the adolescents into four weight groups: underweight (<5th percentile), normal weight (5the84th percentile), overweight (85the94th percentile) and obesity (95th percentile).
2.4. Statistical methods The statistical analysis was performed using SPSS 21.0 (IBM SPSS Statistics). A p value <0.05 was considered statically significant. The Chi-square test was used to test the association between two categorical variables. The t test was used to examine group differences for continuous variables. Due to the nature of right-skewed distribution, the levels of
Please cite this article in press as: Huang Y-F, et al., Relationship Between being Overweight and Iron Deficiency in Adolescents, Pediatrics and Neonatology (2015), http://dx.doi.org/10.1016/j.pedneo.2015.02.003
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Overweight and Iron Deficiency in Adolescents
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PF and SI were log-transformed to approach normal distribution before plotting and statistical testing including t test, ANOVA and Pearson correlation analysis. The ANOVA test was used to examine difference of means for hemoglobin, ferritin, and SI across the four age- and weightgroups. The downward or upward trend of the occurrence of low PF, low SI, and anemia across four weight groups was tested by CochraneeArmitage trend test. The linear association between BMIelogPF and BMIelogSI was presented by Pearson correlation coefficient. A multivariate logistic regression model was conducted separately to associate age, sex and weight groups with the odds of depleted iron store. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Stratified analyses by sex were also performed in addition to the overall analysis.
3. Results 3.1. Basic demographic and laboratory information by two sexes Age, weight classification, hemoglobin, PF, and SI are presented in Table 1 for both male and female adolescent participants. Adolescent girls had significantly lower PF and
Table 1 Distributions of adolescents in different age groups and weight groups and the hemoglobin level, anemia percentage, plasma ferritin, and serum iron levels in both sexes. Male (n Z 772) Age (y) 12e13 54.1 15e16 28.8 18e19 17.1 Weight group Underweight 13.5 Normal weight 46.8 Overweight 17.1 Obesity 22.7 Hemoglobin level (g/dL) Mean SD 14.9 1.2 Anemia No 93.9 Yes 6.1 Plasma ferritin level (mg/L) 15 97.2 <15 2.8 Mean SD 98.2 79.7 Serum iron level (mg/dL) 60 82.9 <60 17.1 Mean SD 96.9 38.4
Female (n Z 1327)
p
22.7 56.6 15.7
<0.001*
14.9 59.3 13.8 12.0
<0.001*
13.4 1.1
<0.001y
91.0 9.0 88.3 11.7 64.7 55.7 79.4 20.6 93.9 41.0
hemoglobin concentrations, and a greater prevalence of anemia and depleted iron store compared with their male counterparts.
3.2. Percentage of depleted iron store across weight groups In female adolescents, the proportion of participants with low SI gradually increased from underweight to obesity weight groups, but the proportion of participants with low PF decreased progressively. However, this step-by-step relationship was not apparent in male adolescents (Figure 1). As shown in Table 2, the percentages of anemia declined significantly as body weight increased from underweight to obesity groups (p Z 0.002). The percentages of low PF had the same trend as the percentages of anemia (p < 0.005), but the percentages of low SI had the opposite trend (p < 0.001).
3.3. Correlation between BMI and the hemoglobin, PF and SI levels In Figure 2, the Pearson correlation coefficient of linear regression was positive for BMIehemoglobin, BMIePF but negative for BMIeSI. All coefficients were statistically significant.
3.4. Factors associated with depleted iron store Table 3 shows the multivariate logistic regression model used to compare the OR (95% CI) of sex, age and weight groups for two dependent variables of PF level < 15 mg/L and SI level < 60 mg/dL. Among total adolescents, female students had more than four times the risk of low PF and two times the risk of low SI compared with male students. The obesity group had a significantly lower risk of low PF (OR Z 0.51, 95% CI: 0.30e0.87), but a higher risk of low SI (OR Z 1.78, 95% CI: 1.34e2.37) compared with normal weight group as shown in Table 3. In a separate model for each sex, the risk of low PF was lower for males but higher for females as age increased.
0.016*
<0.001* <0.001y 0.047* 0.098y
The data are represented as the percentages unless otherwise specified. SD Z standard deviation. * Chi-square test. y Student t test.
Figure 1 The proportion of adolescents with depleted iron store defined by either serum iron (SI) < 60 mg/dL or ferritin <15 mg/L, categorized into four weight groups in two sexes.
Please cite this article in press as: Huang Y-F, et al., Relationship Between being Overweight and Iron Deficiency in Adolescents, Pediatrics and Neonatology (2015), http://dx.doi.org/10.1016/j.pedneo.2015.02.003
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Y.-F. Huang et al Table 2 Age, sex, hemoglobin, ferritin and serum iron levels, percentages of anemia, low ferritin and low serum iron of all participants categorized into four body weight groups. Underweight (n Z 302) Age (y) 12e13 30.5 15e16 45.4 18e19 24.2 Sex Female 65.6 Male 34.4 Hemoglobin level (g/dL). Mean SD 13.9 1.4 % of anemia 10.9 Plasma ferritin level (mg/L) Mean SD 76.9 66.0 % of <15 mg/L 9.9 Serum iron level (mg/dL) Mean SD 97.1 39.4 % of <60 mg/dL 16.2
Normal (n Z 1148)
Overweight (n Z 315)
Obese (n Z 334)
p
35.4 50.3 14.4
42.9 41.3 15.9
45.8 38.6 15.6
<0.001*
68.6 31.4
58.1 41.9
47.6 52.4
<0.001*
13.9 1.3 8.3
14.0 1.3 7.9
14.3 1.3 4.2
<0.001z 0.002y
71.9 62.7 9.5
76.5 64.1 6.7
95.1 83.1 5.1
<0.001z <0.005y
97.8 41.1 17.2
93.6 40.5 22.2
84.5 34.4 26.9
<0.001z <0.001y
The data are represented as the percentages unless otherwise specified. SD Z standard deviation. * Chi-square test. y Cochran-Armitage trend test. z ANOVA.
4. Discussion This present study, based on regular health checkups of adolescents, from junior high schools and senior high schools to a college offers a chance to understand the impact of ID and its potential determinants among adolescents. Similar to previous studies,2,3 we have found female sex as the most important risk factor of ID, possibly because female adolescents have menstrual cycles, which cause regular blood loss. Another remarkable finding is the opposite correlation coefficients of BMIePF and BMIeSI, which may help to understand the controversial association between being overweight and ID. As shown in Figure 1, the overweight/obese female adolescents had a lower proportion of low PF level, but a greater proportion of low SI level than normal-weight and underweight participants. As shown in Figure 2, the Pearson correlation coefficient is significantly positive for BMIePF, but negative for BMIeSI. Both results indicate that overweight/obese adolescents appear to have a lower risk of low PF level but higher risk of low SI level. Table 2 also shows the same trend that the percentages of low PF significantly declined but the percentages of low SI rose as BMI increased from underweight to obesity groups. Therefore, the relationship between being overweight/obese and depleted iron stores could be characterized in opposite ways, depending on which test is used to define the iron status. If we define ID by SI level, being overweight/obese may be a risk factor of ID, but if we define ID by PF, being overweight/obese is not a risk factor. The trend for the percentages of anemia significantly declined as weight group changed from underweight to obesity group (Table 2), which corroborates the previous conclusion that older female adolescents may suffer from
higher possibility of anemia due to regular blood loss from menstrual cycles.3 Moreover, the trend for the percentages of low PF across four weight groups was the same as the trend for anemia, but the trend for percentages of low SI was opposite. This further indicates that PF would be more appropriate than SI to diagnose ID. However, some studies using ferritin to define ID reached the different conclusion that obesity was a risk factor of ID.11,12 We carefully reviewed these references and found they had used other indicator(s) besides ferritin to define ID. For example, Moayeri et al11 defined ID as serum ferritin below 12 ng/mL and transferrin saturation index below 16%. Nead et al12 used three laboratory measures of iron status (i.e., transferrin saturation, free erythrocyte protoporphyrin levels, and serum ferritin levels) and a child was considered iron deficient if two of three values were abnormal for age and gender. CepedaLopez et al14 used not only SI but also elevated total iron-binding capacity and low percentage transferring saturation. From the abovementioned studies, we found using other parameters rather than PF or adding other tests to define ID could significantly change the results. This may be why our conclusion contradicts those of previous studies. Among many diagnostic tests, PF measurement has been proposed as an accurate test to assess human body iron stores because of its high sensitivity and specificity.20e23,30e32 The World Health Organization also clearly states that ferritin is positively correlated with body iron stores.27 Some papers even indicate that serum ferritin was the best single indicator for assessing body iron store.30e32 Adding another test such as serum transferrin receptor or mean corpuscular volume measurement did not improve the accuracy of ID diagnosis.24
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Overweight and Iron Deficiency in Adolescents
5 ID may have some potential adverse effects in adolescents, such as impaired learning capability or cognitive function.5,7 Therefore, the biological effects of ID on learning capacity are strong enough to justify interventions to improve iron status.4 One clinical trial in Switzerland found that a low-dose iron supplementation could improve fatigue in menstruating women with low PF levels.33 We suggest that schools play a more active role in providing adolescents with adequate nutrition and appropriate health education. Female adolescents may have their iron status routinely checked to find ID earlier.
4.1. Limitations
Figure 2 The correlation coefficients for body mass index (BMI)ehemoglobin, BMIeplasma ferritin, and BMIeserum iron.
There were some limitations in this study. First, this crosssectional study used a convenient sample from five schools in southern Taiwan. Because the study population was not based on a well-designed population-based sampling, the representativeness of the ID prevalence in the general population might be negatively affected. Second, because this study was based on routine health checkup for adolescent students entering schools, we did not perform sophisticated laboratory tests to define ID. However, this study may provide a cost-effective solution for physicians to detect the depleted iron store, especially in settings where sophisticated laboratory testing is unaffordable. Third, PF is an acute phase protein; the presence of infection may affect its reliability in the diagnosis. However, CRP levels were not checked in this study and no corrections were done to control the confounding effect of inflammation because of budgetary limitations. Fortunately, the participants were students regularly attending the schools and no ill status was recorded. One previous study has affirmed that low levels of inflammation had little influence on ferritin distribution.34 Fourth, obesity has been thought to be a chronic inflammation that may increase PF level independently of body iron stores, and the prevalence of ID among obesity could be underestimated if not correcting PF level.35 However, even under the possible effect from obesity-related inflammation, we still observed a reduced risk of lower PF level in the overweight group compared with the underweight group. Thus, the confounding effect due to infection or obesity would be not a significant concern in this study.
Table 3 Odds ratios (95% confidence intervals) of sex, age, and weight groups for association with low plasma ferritin or serum iron levels. Plasma ferritin <15 mg/L
Independent variables Total Sex Female vs. male Age group (y) 15e16 vs. 12e13 18e19 vs. 12e13 Weight group Under vs. normal Over vs. normal Obese vs. normal
4.43 (2.78e7.07)
Male
Female
Serum iron < 60 mg/dL Total
Male
Female
1.83 (1.43e2.35)
0.93 (0.64e1.34) 0.18 (0.04e0.77) 1.22 (0.81e1.85) 0.34 (0.26e0.44) 0.20 (0.11e0.36) 0.46 (0.34e0.62) 1.31 (0.83e2.07) 0.15 (0.02e1.13) 1.88 (1.13e3.13) 0.64 (0.47e0.88) 0.09 (0.03e0.25) 1.20 (0.82e1.74) 1.05 (0.69e1.61) 0.49 (0.11e2.17) 1.20 (0.76e1.89) 0.94 (0.66e1.32) 0.99 (0.52e1.88) 0.93 (0.62e1.39) 0.68 (0.42e1.11) 0.19 (0.03e1.45) 0.89 (0.54e1.49) 1.38 (1.02e1.87) 1.95 (1.18e3.23) 1.17 (0.79e1.74) 0.51 (0.30e0.87) 0.73 (0.26e2.06) 0.60 (0.32e1.11) 1.78 (1.34e2.37) 1.77 (1.11e2.82) 2.10 (1.44e3.06)
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5. Conclusion The relationship between being overweight and depleted iron store depends on which indicator is used to define the iron deficiency. Being overweight or obese would not be a risk factor of ID in adolescents, if ID were defined by PF rather than SI level.
Conflicts of interest All contributing authors declare no conflicts of interest.
Acknowledgments We greatly appreciate the help of the nursing staff at the five participating schools and the health checkup team of Pingtung Christian Hospital for data collection.
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Y.-F. Huang et al 14. Cepeda-Lopez AC, Osendarp SJ, Melse-Boonstra A, Aeberli I, Gonzalez-Salazar F, Feskens E, et al. Sharply higher rates of iron deficiency in obese Mexican women and children are predicted by obesity-related inflammation rather than by differences in dietary iron intake. Am J Clin Nutr 2011;93: 975e83. 15. Pinhas-Hamiel O, Newfield RS, Koren I, Agmon A, Lilos P, Phillip M. Greater prevalence of iron deficiency in overweight and obese children and adolescents. Int J Obes Relat Metab Disord 2003;27:416e8. 16. Leenstra T, Kariuki SK, Kurtis JD, Oloo AJ, Kager PA, ter Kuile FO. Prevalence and severity of anemia and iron deficiency: cross-sectional studies in adolescent schoolgirls in western Kenya. Eur J Clin Nutr 2004;58:681e91. 17. Akramipour R, Rezaei M, Rahimi Z. Prevalence of iron deficiency anemia among adolescent schoolgirls from Kermanshah, Western Iran. Hematology 2008;13:352e5. 18. Kurniawan YA, Muslimatun S, Achadi EL, Sastroamidjojo S. Anaemia and iron deficiency anaemia among young adolescent girls from the peri urban coastal area of Indonesia. Asia Pac J Clin Nutr 2006;15:350e6. 19. Eicher-Miller HA, Mason AC, Weaver CM, McCabe GP, Boushey CJ. Food insecurity is associated with iron deficiency anemia in US adolescents. Am J Clin Nutr 2009;90:1358e71. 20. Lewis DK, Whitty CJ, Epino H, Letsky EA, Mukiibi JM, van den Broek NR. Interpreting tests for iron deficiency among adults in a high HIV prevalence African setting: routine tests may lead to misdiagnosis. Trans R Soc Trop Med Hyg 2007;101:613e7. 21. Phiri KS, Calis JC, Siyasiya A, Bates I, Brabin B, van Hensbroek MB. New cut-off values for ferritin and soluble transferrin receptor for the assessment of iron deficiency in children in a high infection pressure area. J Clin Pathol 2009; 62:1103e6. 22. Ong KH, Tan HL, Lai HC, Kuperan P. Accuracy of various iron parameters in the prediction of iron deficiency in an acute care hospital. Ann Acad Med Singapore 2005;34:437e40. 23. Uen WC, Ling KE. Evaluation of the accuracy and efficiency of iron-related tests in the diagnosis of iron deficiency anemia. J Intern Med 2005;16:269e73 [Article in Chinese, Enlgish abstract]. 24. Chouliaras GL, Premetis E, Tsiftis G, Drosatou P, Papassotiriou I, Stamoulakatou A, et al. Serum transferrin receptors: distribution and diagnostic performance in pre-school children. Blood Cells Mol Dis 2009;43:163e8. 25. WHO/UNICEF/UNU. Iron deficiency anaemia: assessment, prevention and control. A guide for programme managers. Geneva: World Health Organization; 2001. 26. Lin JD, Lin PY, Lin LP, Hsu SW, Loh CH, Yen CF, et al. Prevalence and associated risk factors of anemia in children and adolescents with intellectual disabilities. Res Dev Disabil 2010;31: 25e32. 27. WHO. Serum ferritin concentrations for the assessment of iron status and iron deficiency in populations. Vitamin and Mineral Nutrition Information System. Geneva: World Health Organization; 2011. 28. Sun A, Lin HP, Wang YP, Chiang CP. Significant association of deficiency of hemoglobin, iron and vitamin B12, high homocysteine level, and gastric parietal cell antibody positivity with atrophic glossitis. J Oral Pathol Med 2012;41:500e4. 29. Hsieh PL, FitzGerald M. Childhood obesity in Taiwan: review of the Taiwanese literature. Nurs Health Sci 2005;7:134e42. 30. Ren Y, Walczyk T. Quantification of ferritin bound iron in human serum using species-specific isotope dilution mass spectrometry. Metallomics 2014;6:1709e17. 31. Zaribaf F, Entezari MH, Hassanzadeh A, Mirzaian S. Association between dietary iron, iron stores, and serum lipid profile in reproductive age women. J Educ Health Promot 2014;3:15.
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7 indicators of total-body iron stores in survey populations: the role of biomarkers for the acute phase response. Am J Clin Nutr 2006;84:1498e505. 35. Gartner A, Berger J, Bour A, El Ati J, Traissac P, Landais E, et al. Assessment of iron deficiency in the context of the obesity epidemic: importance of correcting serum ferritin concentrations for inflammation. Am J Clin Nutr 2013;98: 821e6.
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Pediatrics and Neonatology (2015) xx, 1e7
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ORIGINAL ARTICLE
Relationship Between being Overweight and Iron Deficiency in Adolescents Ya-Fang Huang a, Teck-Siang Tok b, Chin-Li Lu c, Hsing-Ching Ko d, Min-Yu Chen d,*, Solomon Chih-Cheng Chen d,e,* a
Department of Clinical Laboratory, Pingtung Christian Hospital, Pingtung City, Taiwan Department of Pediatrics, Pingtung Christian Hospital, Pingtung City, Taiwan c Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan d Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan e School of Medicine, Taipei Medical University, Taipei City, Taiwan b
Received Jun 24, 2014; received in revised form Dec 10, 2014; accepted Feb 13, 2015
Available online - - -
Key Words body mass index; ferritin; obese; serum iron
Objective: Being overweight has been considered to be a risk factor of iron deficiency (ID). The objective of this study was to examine the relationship between being overweight and body iron status among Taiwanese adolescents. Methods: A total of 2099 adolescents (1327 female) aged 12e19 years from four middle schools and one college in southern Taiwan participated in this study. Data on sex, age, body weight, height, hemoglobin concentration, plasma ferritin (PF), and serum iron (SI) levels were collected. According to the age- and sex-specific body mass index (BMI) percentiles, the participants were divided into four weight groups: underweight (<5th percentile), normal weight (5e84th percentile), overweight (85e94th percentile), and obese (95th percentile). A multivariate logistic regression model was used to estimate the odds ratio (OR) and the 95% confidence interval (CI) for each factor. Results: The correlation coefficients of linear regression were positive for BMIehemoglobin and BMIePF, but negative for BMIeSI. Compared with the normal-weight group, the obese group had a lower risk of PF level <15 mg/L with an OR (95% CI) of 0.51 (0.30e0.87) but a higher risk of SI <60 mg/dL with an OR (95% CI) of 1.78 (1.34e2.37). The percentages of low PF declined as BMI increased, but the percentages of low SI rose, from underweight to obesity groups.
* Corresponding authors. Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, 539 Zhongxiao Road, East District, Chia-Yi City, 60002, Taiwan. E-mail addresses: [email protected] (M.-Y. Chen), [email protected] (S.C.-C. Chen). http://dx.doi.org/10.1016/j.pedneo.2015.02.003 1875-9572/Copyright ª 2015, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved.
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Y.-F. Huang et al Conclusion: The relationship between being overweight and depleted iron store depends on which indicator is used to define the iron deficiency. Being overweight or obese would not be a risk factor of ID in adolescents, if ID were defined by PF rather than SI level. Copyright ª 2015, Taiwan Pediatric Association. Published by Elsevier Taiwan LLC. All rights reserved.
1. Introduction
2. Methods
Iron deficiency (ID) may be the most common form of nutritional deficiency worldwide and it is a significant public health problem in both developed and undeveloped countries.1 In a nationally representative cross-sectional health study in the USA, the prevalence of ID was 9e11% for adolescent girls and women of childbearing age, corresponding to approximately 8 million women with ID.2 One previous national study in Taiwan showed that the prevalence of ID was 2e6% in adolescent males and 9e10% in adolescent females.3 ID may cause adverse effects, including reduced work capacity,4 delayed mental and physical development in children,5 lower cognitive or behavioral function,6,7 and impaired sensorimotor function.8 Since ID is an important public health issue, examining its determinants is important to public health research. Several predisposing factors have been mentioned in the literature, such as female sex, parasite infestation,9 and Helicobacter pylori infection.10 Some previous studies have suggested being overweight as a risk factor for ID.11e15 However, that being overweight may be a risk for ID is contrary to our general understanding, because ID is a micronutrient deficiency that usually occurs in the context of poor nutritional status. For example, the prevalence of ID is often higher in developing countries and it is also associated with lower socioeconomic status.1,16e19 One study in Indonesia found that thinner adolescents have a five-fold higher risk of suffering from ID anemia compared with nonthin adolescents.18 Another study in the USA found that children in households with inadequate food had an almost three-fold higher risk of ID than children in households with adequate food.19 Moreover, the causal mechanism of being overweight for ID still needs further study for clarification. One challenge to study the risk factor of ID is the diversity of ID diagnosis, for there are many tests but no consensus. Many indicators, such as plasma ferritin (PF), serum iron (SI), soluble transferrin receptor, zinc protoporphyrin, and mean corpuscular volume, have been used to diagnose ID through a single test or a combination of several tests.20e25 Combining several tests to diagnose ID may be appropriate in academic study, but this is not cost efficient for clinical practice or public health intervention. In practice, SI and PF are the two most frequently used single tests. However, their relationship with being overweight has not been well studied or compared. Thus, the objectives of this study were to examine the relationship between being overweight and body iron status in Taiwanese adolescents by comparing the two tests of SI and PF.
2.1. Ethics statement The Ethics Review Board of Pingtung Christian Hospital approved the protocol and informed consent prior to the commencement of this study. All participants or their parents provided written informed consent. All data were collected for statistical analysis only, and no personal identification was revealed or compromised.
2.2. Study population This study was based on routine health checkups that were given to adolescents when they entered school. A total of 2099 adolescents (1327 girls) from one junior high school (786 students, age 12e13 years), three senior high schools (973 students, aged 15e16 years), and one college (340 students, age 18e19 years) in Pingtung County in southern Taiwan participated in this survey in September 2010.
2.3. Laboratory data and definitions The physical examination and blood sampling were performed after an overnight fast. Bodyweight, height, blood hemoglobin, SI, and PF levels were measured. Venous blood was taken for biochemical analyses, which were performed at the certified clinical laboratory of Pingtung Christian Hospital using a Beckman Coulter LX-20 autoanalyzer (Beckman Coulter, Brea, CA, USA). All technicians were blind to the demographic data and body mass index (BMI) of the participants. We followed the previous studies and World Health Organization recommendations to define anemia as a hemoglobin concentration under 13 g/dL in males or 12 g/dL in females.25,26 Depleted iron store was defined as either a PF level <15 mg/L25,27 or SI level <60 mg/ dL.14,28 According to sex- and age-specific BMI criteria,29 we classified all of the adolescents into four weight groups: underweight (<5th percentile), normal weight (5the84th percentile), overweight (85the94th percentile) and obesity (95th percentile).
2.4. Statistical methods The statistical analysis was performed using SPSS 21.0 (IBM SPSS Statistics). A p value <0.05 was considered statically significant. The Chi-square test was used to test the association between two categorical variables. The t test was used to examine group differences for continuous variables. Due to the nature of right-skewed distribution, the levels of
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PF and SI were log-transformed to approach normal distribution before plotting and statistical testing including t test, ANOVA and Pearson correlation analysis. The ANOVA test was used to examine difference of means for hemoglobin, ferritin, and SI across the four age- and weightgroups. The downward or upward trend of the occurrence of low PF, low SI, and anemia across four weight groups was tested by CochraneeArmitage trend test. The linear association between BMIelogPF and BMIelogSI was presented by Pearson correlation coefficient. A multivariate logistic regression model was conducted separately to associate age, sex and weight groups with the odds of depleted iron store. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Stratified analyses by sex were also performed in addition to the overall analysis.
3. Results 3.1. Basic demographic and laboratory information by two sexes Age, weight classification, hemoglobin, PF, and SI are presented in Table 1 for both male and female adolescent participants. Adolescent girls had significantly lower PF and
Table 1 Distributions of adolescents in different age groups and weight groups and the hemoglobin level, anemia percentage, plasma ferritin, and serum iron levels in both sexes. Male (n Z 772) Age (y) 12e13 54.1 15e16 28.8 18e19 17.1 Weight group Underweight 13.5 Normal weight 46.8 Overweight 17.1 Obesity 22.7 Hemoglobin level (g/dL) Mean SD 14.9 1.2 Anemia No 93.9 Yes 6.1 Plasma ferritin level (mg/L) 15 97.2 <15 2.8 Mean SD 98.2 79.7 Serum iron level (mg/dL) 60 82.9 <60 17.1 Mean SD 96.9 38.4
Female (n Z 1327)
p
22.7 56.6 15.7
<0.001*
14.9 59.3 13.8 12.0
<0.001*
13.4 1.1
<0.001y
91.0 9.0 88.3 11.7 64.7 55.7 79.4 20.6 93.9 41.0
hemoglobin concentrations, and a greater prevalence of anemia and depleted iron store compared with their male counterparts.
3.2. Percentage of depleted iron store across weight groups In female adolescents, the proportion of participants with low SI gradually increased from underweight to obesity weight groups, but the proportion of participants with low PF decreased progressively. However, this step-by-step relationship was not apparent in male adolescents (Figure 1). As shown in Table 2, the percentages of anemia declined significantly as body weight increased from underweight to obesity groups (p Z 0.002). The percentages of low PF had the same trend as the percentages of anemia (p < 0.005), but the percentages of low SI had the opposite trend (p < 0.001).
3.3. Correlation between BMI and the hemoglobin, PF and SI levels In Figure 2, the Pearson correlation coefficient of linear regression was positive for BMIehemoglobin, BMIePF but negative for BMIeSI. All coefficients were statistically significant.
3.4. Factors associated with depleted iron store Table 3 shows the multivariate logistic regression model used to compare the OR (95% CI) of sex, age and weight groups for two dependent variables of PF level < 15 mg/L and SI level < 60 mg/dL. Among total adolescents, female students had more than four times the risk of low PF and two times the risk of low SI compared with male students. The obesity group had a significantly lower risk of low PF (OR Z 0.51, 95% CI: 0.30e0.87), but a higher risk of low SI (OR Z 1.78, 95% CI: 1.34e2.37) compared with normal weight group as shown in Table 3. In a separate model for each sex, the risk of low PF was lower for males but higher for females as age increased.
0.016*
<0.001* <0.001y 0.047* 0.098y
The data are represented as the percentages unless otherwise specified. SD Z standard deviation. * Chi-square test. y Student t test.
Figure 1 The proportion of adolescents with depleted iron store defined by either serum iron (SI) < 60 mg/dL or ferritin <15 mg/L, categorized into four weight groups in two sexes.
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Y.-F. Huang et al Table 2 Age, sex, hemoglobin, ferritin and serum iron levels, percentages of anemia, low ferritin and low serum iron of all participants categorized into four body weight groups. Underweight (n Z 302) Age (y) 12e13 30.5 15e16 45.4 18e19 24.2 Sex Female 65.6 Male 34.4 Hemoglobin level (g/dL). Mean SD 13.9 1.4 % of anemia 10.9 Plasma ferritin level (mg/L) Mean SD 76.9 66.0 % of <15 mg/L 9.9 Serum iron level (mg/dL) Mean SD 97.1 39.4 % of <60 mg/dL 16.2
Normal (n Z 1148)
Overweight (n Z 315)
Obese (n Z 334)
p
35.4 50.3 14.4
42.9 41.3 15.9
45.8 38.6 15.6
<0.001*
68.6 31.4
58.1 41.9
47.6 52.4
<0.001*
13.9 1.3 8.3
14.0 1.3 7.9
14.3 1.3 4.2
<0.001z 0.002y
71.9 62.7 9.5
76.5 64.1 6.7
95.1 83.1 5.1
<0.001z <0.005y
97.8 41.1 17.2
93.6 40.5 22.2
84.5 34.4 26.9
<0.001z <0.001y
The data are represented as the percentages unless otherwise specified. SD Z standard deviation. * Chi-square test. y Cochran-Armitage trend test. z ANOVA.
4. Discussion This present study, based on regular health checkups of adolescents, from junior high schools and senior high schools to a college offers a chance to understand the impact of ID and its potential determinants among adolescents. Similar to previous studies,2,3 we have found female sex as the most important risk factor of ID, possibly because female adolescents have menstrual cycles, which cause regular blood loss. Another remarkable finding is the opposite correlation coefficients of BMIePF and BMIeSI, which may help to understand the controversial association between being overweight and ID. As shown in Figure 1, the overweight/obese female adolescents had a lower proportion of low PF level, but a greater proportion of low SI level than normal-weight and underweight participants. As shown in Figure 2, the Pearson correlation coefficient is significantly positive for BMIePF, but negative for BMIeSI. Both results indicate that overweight/obese adolescents appear to have a lower risk of low PF level but higher risk of low SI level. Table 2 also shows the same trend that the percentages of low PF significantly declined but the percentages of low SI rose as BMI increased from underweight to obesity groups. Therefore, the relationship between being overweight/obese and depleted iron stores could be characterized in opposite ways, depending on which test is used to define the iron status. If we define ID by SI level, being overweight/obese may be a risk factor of ID, but if we define ID by PF, being overweight/obese is not a risk factor. The trend for the percentages of anemia significantly declined as weight group changed from underweight to obesity group (Table 2), which corroborates the previous conclusion that older female adolescents may suffer from
higher possibility of anemia due to regular blood loss from menstrual cycles.3 Moreover, the trend for the percentages of low PF across four weight groups was the same as the trend for anemia, but the trend for percentages of low SI was opposite. This further indicates that PF would be more appropriate than SI to diagnose ID. However, some studies using ferritin to define ID reached the different conclusion that obesity was a risk factor of ID.11,12 We carefully reviewed these references and found they had used other indicator(s) besides ferritin to define ID. For example, Moayeri et al11 defined ID as serum ferritin below 12 ng/mL and transferrin saturation index below 16%. Nead et al12 used three laboratory measures of iron status (i.e., transferrin saturation, free erythrocyte protoporphyrin levels, and serum ferritin levels) and a child was considered iron deficient if two of three values were abnormal for age and gender. CepedaLopez et al14 used not only SI but also elevated total iron-binding capacity and low percentage transferring saturation. From the abovementioned studies, we found using other parameters rather than PF or adding other tests to define ID could significantly change the results. This may be why our conclusion contradicts those of previous studies. Among many diagnostic tests, PF measurement has been proposed as an accurate test to assess human body iron stores because of its high sensitivity and specificity.20e23,30e32 The World Health Organization also clearly states that ferritin is positively correlated with body iron stores.27 Some papers even indicate that serum ferritin was the best single indicator for assessing body iron store.30e32 Adding another test such as serum transferrin receptor or mean corpuscular volume measurement did not improve the accuracy of ID diagnosis.24
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5 ID may have some potential adverse effects in adolescents, such as impaired learning capability or cognitive function.5,7 Therefore, the biological effects of ID on learning capacity are strong enough to justify interventions to improve iron status.4 One clinical trial in Switzerland found that a low-dose iron supplementation could improve fatigue in menstruating women with low PF levels.33 We suggest that schools play a more active role in providing adolescents with adequate nutrition and appropriate health education. Female adolescents may have their iron status routinely checked to find ID earlier.
4.1. Limitations
Figure 2 The correlation coefficients for body mass index (BMI)ehemoglobin, BMIeplasma ferritin, and BMIeserum iron.
There were some limitations in this study. First, this crosssectional study used a convenient sample from five schools in southern Taiwan. Because the study population was not based on a well-designed population-based sampling, the representativeness of the ID prevalence in the general population might be negatively affected. Second, because this study was based on routine health checkup for adolescent students entering schools, we did not perform sophisticated laboratory tests to define ID. However, this study may provide a cost-effective solution for physicians to detect the depleted iron store, especially in settings where sophisticated laboratory testing is unaffordable. Third, PF is an acute phase protein; the presence of infection may affect its reliability in the diagnosis. However, CRP levels were not checked in this study and no corrections were done to control the confounding effect of inflammation because of budgetary limitations. Fortunately, the participants were students regularly attending the schools and no ill status was recorded. One previous study has affirmed that low levels of inflammation had little influence on ferritin distribution.34 Fourth, obesity has been thought to be a chronic inflammation that may increase PF level independently of body iron stores, and the prevalence of ID among obesity could be underestimated if not correcting PF level.35 However, even under the possible effect from obesity-related inflammation, we still observed a reduced risk of lower PF level in the overweight group compared with the underweight group. Thus, the confounding effect due to infection or obesity would be not a significant concern in this study.
Table 3 Odds ratios (95% confidence intervals) of sex, age, and weight groups for association with low plasma ferritin or serum iron levels. Plasma ferritin <15 mg/L
Independent variables Total Sex Female vs. male Age group (y) 15e16 vs. 12e13 18e19 vs. 12e13 Weight group Under vs. normal Over vs. normal Obese vs. normal
4.43 (2.78e7.07)
Male
Female
Serum iron < 60 mg/dL Total
Male
Female
1.83 (1.43e2.35)
0.93 (0.64e1.34) 0.18 (0.04e0.77) 1.22 (0.81e1.85) 0.34 (0.26e0.44) 0.20 (0.11e0.36) 0.46 (0.34e0.62) 1.31 (0.83e2.07) 0.15 (0.02e1.13) 1.88 (1.13e3.13) 0.64 (0.47e0.88) 0.09 (0.03e0.25) 1.20 (0.82e1.74) 1.05 (0.69e1.61) 0.49 (0.11e2.17) 1.20 (0.76e1.89) 0.94 (0.66e1.32) 0.99 (0.52e1.88) 0.93 (0.62e1.39) 0.68 (0.42e1.11) 0.19 (0.03e1.45) 0.89 (0.54e1.49) 1.38 (1.02e1.87) 1.95 (1.18e3.23) 1.17 (0.79e1.74) 0.51 (0.30e0.87) 0.73 (0.26e2.06) 0.60 (0.32e1.11) 1.78 (1.34e2.37) 1.77 (1.11e2.82) 2.10 (1.44e3.06)
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5. Conclusion The relationship between being overweight and depleted iron store depends on which indicator is used to define the iron deficiency. Being overweight or obese would not be a risk factor of ID in adolescents, if ID were defined by PF rather than SI level.
Conflicts of interest All contributing authors declare no conflicts of interest.
Acknowledgments We greatly appreciate the help of the nursing staff at the five participating schools and the health checkup team of Pingtung Christian Hospital for data collection.
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