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Community and International Nutrition

Bioavailable Dietary Iron Is Associated with Hemoglobin Concentration in Mexican Preschool Children^1,2

³ Research Center on Nutrition and Health, National Institute of Public Health, Cuernavaca, Morelos, 62508 Mexico and ⁴ HarvestPlus, International Food Policy Research Institute, Washington, DC 20006-1002

^* To whom correspondence should be addressed. E-mail: jrivera{at}correo.insp.mx.

	ABSTRACT

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
The objective of this study was to estimate the amount of bioavailable iron (FeBIO) in the diet of Mexican children aged 12–59 mo through the application of algorithms that use dietary variables and analyze the association between estimated FeBIO and hemoglobin (Hb) concentration. Data were analyzed for 919 children aged 12–59 mo old who participated in a national probabilistic survey on nutrition, in which a 24-h dietary recall was applied and Hb concentration was determined through the use of portable photometers. Dietary intakes were determined for total iron, heme and nonheme iron, vitamin C, phytates, and meat (red meat, poultry, and fish). Using these dietary variables and distinct scenarios on body iron reserves, we used algorithms to estimate the amount of FeBIO in the diet. Linear regression models were adjusted to evaluate the association between FeBIO and Hb. The mean iron intake was 6.2 ± 4.4 mg/d and the mean estimated FeBIO ranged between 0.14 and 0.37 mg/d depending on different assumptions about iron reserves, representing 2.7–6.1% of total iron intake. The Hb concentration, adjusted for altitude and presence of diarrhea, was positively associated with FeBIO in children 12–23 mo old (P < 0.05) but not in children 24–59 mo old. The estimated FeBIO is low in relation to physiological requirements and is compatible with existing high iron deficiency prevalence rates in Mexico. Although Hb is not a specific indicator of iron status, it was significantly associated with FeBIO.

	Introduction

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

Anemia is the most serious form of iron deficiency, a condition with adverse effects on cognitive and psychomotor development in children 2 y of age (4–7), learning capacity (8), behavior, physical capacity, resistance to infections, infant mortality (9), and birth weight of children whose mothers suffer anemia (10). In Mexico, 27.2% of children 1–4 y of age were anemic and 53.0% were iron deficient in 1999 (11,12).

Among the various causes of iron deficiency anemia in children 5 y is the insufficient dietary intake of iron or its low bioavailability during this stage of high requirements due to rapid growth (13–18). Algorithms have been developed to estimate the bioavailability of iron in the diet. These algorithms take into account the effects of some or all of the following dietary factors: 1) meat (fish, poultry, and red meat) as a source of heme iron that is well absorbed and increases the absorption of nonheme iron (6,19); 2) vitamin C, which acts as an iron-reducing agent or bonds with the iron to form an easily absorbed complex (20,21); 3) phytate, which acts as a chelator of iron and other mineral ions, inhibiting their absorption (20); and 4) tea, which reduces absorption of nonheme iron (depending on the concentration of polyphenols and the composition of the meal) (21). Such algorithms have been used to evaluate the bioavailability of iron in diets in several countries (22–29). The algorithms, derived from clinical isotope tracer studies of iron absorption from foods or representative meals, are presumably applicable to estimating dietary iron intake adequacy at the population level, but few population-based studies to date have demonstrated a relationship between estimated bioavailable iron (FeBIO)⁵ intake and indicators of iron status. Despite the common wisdom suggesting that iron intake and anemia should be correlated, the only study examining associations between iron intake and iron status in children did not find an association (8), perhaps because the authors did not take into account bioavailability of iron. In a previous study among adults, a significant positive association was found between FeBIO intake and hemoglobin (Hb) concentration (27) in Bangladeshi women; in another study in Chinese women, no significant association was found (18). The applicability of clinically derived data on iron bioavailability to population iron status needs to be demonstrated. If such associations existed, it would provide further justification for interventions designed to increase bioavailability of dietary iron, such as through dietary modification or diversification.

Consumption of elevated quantities of cow's milk in preschool children may also cause iron deficiency due to its low iron content, displacement of other foods rich in iron, its high calcium content that inhibits iron absorption, and microhemorrhages in children <12 mo due to irritation of the intestinal mucous (30–33).

There is little research in the Mexican population that has quantified the consumption of heme and nonheme iron separately and which has estimated the amount of FeBIO in the diet (13); no research to our knowledge has done so in a probabilistic national sample. Furthermore, few studies in the world have been able to relate the association between FeBIO, estimated by algorithms, and biochemical indicators of iron status in preschool children (18,27).

Due to the fact that only a fraction of total iron intake is bioavailable, it is important to consider its bioavailability for dietary recommendations and for the design of programs aimed at improving iron status of the population, especially given the high prevalence of iron deficiency and anemia in Mexico. The objectives of this study were to determine total iron intakes, including heme and nonheme iron, and estimate the amount of FeBIO in the diet of Mexican children between 12 and 59 mo of age. Another objective was to study the association between estimated bioavailable dietary iron and Hb concentration.

	Materials and Methods

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
    Study population. A secondary analysis was conducted using data from a subsample of children between 12 and 59 mo of age included in the 2nd Mexican National Nutrition Survey, a probabilistic survey carried out between October 1998 and March 1999. This survey was designed to be representative at the national level, as well as for rural and urban areas and 4 regions: north, center, south, and the Mexico City metropolitan area. Detailed descriptions of the survey's design and methodology have been published elsewhere (34). The selection scheme was multi-staged, stratified, and by clusters. The total survey sample size was 17,944 households. Within each household, general information was collected on all members <5 y (5526 children). Dietary information was obtained in a random subsample (n = 1072) of children between 12 and 59 mo of age corresponding to one-fifth of the total sample of children. The present analysis included data from children with valid data on Hb concentration and diet (n = 919). Informed consent was obtained from each child's parent or guardian for the child's participation in the study. The survey protocol was approved by the Ethics Committee of the National Institute of Public Health, Mexico.

    Data collection. The following information was used in the analysis: Hb concentration in blood; dietary intake of heme and nonheme iron, phytate, vitamin C, and cow's milk; age; anthropometric indicators on the child's nutritional status (Z score of weight-for-height, height-for-age, and weight-for-age); socioeconomic level; and data on morbidity over the previous 2-wk period.

The survey methods used to collect these data have been described in detail and are briefly summarized here. Hb was measured in capillary blood samples using portable photometers (Hemocue Becton Dickinson) and anemia was defined using the cut-off point of 110.0 g/L (35), adjusting in accordance with the altitude above sea level (36) of the place of residence.

Dietary information was collected through a 24-h dietary recall obtained by trained personnel who interviewed the person responsible for the child's meals. Intakes of energy, iron, vitamin C, and phytate at each mealtime (breakfast, lunch, snacks, and dinner) were determined. The food composition table used to calculate the amount of nutrients consumed was a compilation made by the National Institute of Public Health from various standard estimates of nutritional contents of foods from different sources (37). Because we did not have enough information about phytate content in Mexican foods, we used dietary composition data from other populations (29,38).

We assumed that the nonheme iron content in meats was 60 and 100% in the remaining foods (39). In the case of preparations that included various food elements, the amount of each type of iron was calculated for each ingredient to obtain the total content for the preparation. Milk was expressed in milliliters; powdered milk consumed was converted to its fluid form. Consumption was categorized as low (<600 mL) and high (600 mL) based on the results of diverse studies on the association between high milk consumption and Hb concentration (6,33). Meat consumption was expressed as grams consumed of red meats, poultry, and fish.

FeBIO is the amount of iron absorbed and utilizable, which depends of several factors, including an individual's iron status. We estimated FeBIO based on the algorithm developed by Bhargava and colleagues (27), which takes into account information on dietary iron content and dietary factors that influence iron absorption for distinct levels of body iron reserves (Table 1). This algorithm was considered the most adequate given the information available; those algorithms that require information on the concentration of serum ferritin (28,29) were discarded, because this information was not available from the survey. The Bhargava method adjusts for consumption of enhancing factors of iron absorption (EF; sum of milligrams of vitamin C and grams of meat) and phytate at each mealtime. Total daily FeBIO was obtained by summing total daily bioavailable nonheme iron and bioavailable heme iron. The FeBIO was also expressed as the proportion of total dietary iron that is bioavailable (percent FeBIO). The algorithm used is based on those published by Monsen and Balintfy (23) and Tseng et al. (26), but as opposed to those that assume an adequate body iron reserve (500 mg), Bhargava et al. (27) present the results considering 3 possible scenarios of iron reserves: 500 mg (adequate reserves), 250 mg (median reserve) in which there are no functional alterations due to iron deficiency, and 0 mg in which functional alterations may already be present due to iron deficiency. The 2 latter reserve scenarios are more appropriate among iron-deficient populations. The adjustment by the amount of tea, proposed by Tseng et al. (26), was omitted, because tea is not a common beverage in the Mexican diet. We also estimated FeBIO as a percentage of the mean physiological requirement for absorbed iron (40).

We excluded a total of 153 observations; 52 with missing data for Hb values and 101 with data points considered outside the valid intervals for the following variables: Hb values <40 or >185 g/L (35) (2 observations); dietary intakes of energy, carbohydrates, proteins, or fats >5 SD from their respective means (45) (95 observations); height-for-age <–5.5 or >3 Z score (42) (4 observations).

    Statistical methods. We used chi-square tests to identify differences (P < 0.05) in anemia prevalence rates between age groups, place of residence (rural vs. urban), and sex. To study the association between FeBIO and Hb concentration, we implemented a multiple linear regression model with Hb concentration as dependent variable, FeBIO as independent variable, and the following covariates: age, high milk consumption, presence of diarrhea, altitude of place of residence, height-for-age Z score, and socioeconomic factor. We constructed a model for all children between 12 and 59 mo of age and separate models for 2 age groups: 12–23 mo and 24–59 mo. We also determined the association between total iron intake and Hb concentration, adjusting for the covariates listed above and in all age groups (results not shown). Finally, we verified normality and variance homogeneity of the residuals and tested for multicolinearity among independent variables in the 3 models.

Analyses using the log transformation form of FeBIO yielded similar results to those found using the nontransformed variable. To facilitate interpretation of the results, we used the nontransformed form in the analyses.

To illustrate the potential impact of FeBIO intake on anemia prevalence in children 12–23 mo, we estimated the area under the normal distribution for values lower than the cut-off value for anemia (Hb < 110 g/L) on the basis of the actual distribution of Hb values in this age group and the distribution based on an estimated mean Hb resulting from doubling the FeBIO. We first estimated the prevalence of anemia in a normal distribution of Hb with the mean concentration and SD observed in the group of children 12–23 mo (Table 2). Likewise, anemia prevalence in the distribution resulting from doubling the FeBIO intake was obtained using the same methodology. The mean Hb value for this estimated distribution was obtained using the regression coefficient of FeBIO on Hb (Table 3) and the SD of Hb (Table 2). Finally, the difference between the estimated prevalences of anemia of the 2 distributions was used as a measure of the potential effect of doubling FeBIO on anemia.

	Results

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
Included in the analysis were 919 children between 12 and 59 mo of age from a national probabilistic sample designed for the study of diet and which included data on dietary intakes and Hb concentration. The study variables did not differ between the group of children included in the analysis and the group from the original sample that were not included due to the absence of Hb data (14% of the original sample). Of the 919 children, 51% were male and 66% were urban residents. Higher anemia prevalence was observed in children between 12 and 23 mo of age than in those between 24 and 59 mo (P < 0.05). The prevalences did not differ in the subgroups of 24–35, 36–47, and 48–59 mo of age. For this reason, data were stratified by the 2 age groups, 12–23 and 24–59 mo, with differing anemia prevalence rates. The prevalence of anemia did not differ between boys (22.2%) and girls (24.5%) or between children living in rural (22.5%) and urban (22.3%) areas. The percentage of children with diarrhea during the 2 wk before the interview was 16.8% in the 12–23-mo age group and 6.6% in the 24–59-mo age group.

With respect to FeBIO intakes, these children's diets were characterized by a low intake of heme iron and an elevated intake of phytate (Table 2). Cow's milk consumption was common but did not reach particularly elevated volumes. We observed impaired linear growth (height-for-age Z score close to –1) with no indication of wasting (low weight-for-height).

The mean estimated FeBIO ranged between 0.14 and 0.28 mg/d for the children aged 12–23 mo and between 0.18 and 0.37 mg/d for those 24–59 mo old (Table 3). Iron bioavailability ranged from 2.7 to 6.1% for the different body iron reserve and age groups and the percentage of physiological iron requirements ranged between 26 and 60%.

For the multivariate analysis of the determinants of Hb concentration, there was complete information for 875 subjects for the variables included in the equation, based on a biological model supported by published evidence (8,16,27,33,36) (Table 4). Children are expected to have iron stores <150 mg, so we used the FeBIO with 250 mg of body iron reserves for children age 24–59 mo as the independent variable for the model. For children 12–23 mo of age, we chose the reserve of 0 mg, because it probably better reflects or is nearer the true body iron reserve in this age group, which presents high rates of anemia and iron deficiency (12). In the model that included all the children, 4 of the 7 adjusted variables (FeBIO intake, age, altitude, and socioeconomic factor) were significantly associated with Hb concentration, whereas 2 additional variables (presence of diarrhea in the previous 2 wk and height-for-age) were marginally associated (P = 0.09 and 0.05, respectively); cow's milk consumption was not significantly associated with Hb. We retained all variables in the model regardless of their P-value.

The estimated effect of doubling the FeBIO intake (from 0.28 to 0.56 mg/d) in children 12–23 mo old was 4.1 g/L of Hb.

We analyzed the interactions between cow's milk consumption and FeBIO, cow's milk consumption and socioeconomic level, and cow's milk consumption and age, but they were not significant and therefore were not included in the final models.

	Discussion

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
The estimated intake of FeBIO in Mexican children ranged between 0.14 and 0.28 mg/d in children 12–23 mo and between 0.18 and 0.37 mg/d in children 2–4 y of age, depending on iron body reserves assumptions. These amounts of estimated absorbed iron are substantially lower than the iron requirements of 0.54 mg/d for the younger children and 0.87 mg/d for the older children (40). The low intake of FeBIO is not due to low intakes of total iron but to low iron bioavailability. The intakes of total iron would be adequate if iron bioavailability were >12%; however, the estimated iron bioavailability was low, ranging between 2.7 and 6.1% depending on the different assumptions of body iron reserves.

The low estimated bioavailability is due in large measure to the fact that only 4.5% of total dietary iron corresponded to heme iron, whereas in other populations, heme iron represents 10–15% of total iron in the diet (47). In addition, Mexican children consume a high amount of iron-absorption inhibitors, especially phytate derived mainly from tortillas and other corn products. For these reasons, the amount of iron in the diet of Mexican children did not satisfy their needs for this micronutrient.

This is the first study to our knowledge that estimates the bioavailability of iron in the diet of Mexican children in a representative sample. Our results for bioavailability of iron are similar to those found in a study of 18–30-mo-old children in rural Mexican communities that used an algorithm based on the Monsen method (13).

We found a positive association between Hb and FeBIO in a multivariate model adjusting for various factors that are determinants of Hb. The association of FeBIO with Hb concentration was greater in children 12–23 mo of age than in older children, suggesting that inadequate dietary intake of FeBIO is a major cause of anemia in younger rather than in older children. The results illustrate a clear positive association between Hb and FeBIO, which confers biological importance to the estimations of iron bioavailability. Further, the magnitude of the association is biologically important; for example, doubling the FeBIO in children 12–23 mo (from 0.28 to 0.56 mg/d) would translate into a Hb increase of 4.1 g/L (from 114.3 to 118.4 g/L). This change in the mean Hb concentration translates into a 10% reduction in anemia.

In a model where total iron intake was included as an independent variable in place of FeBIO, the total iron intake was not significantly associated with Hb. This supports the importance of considering factors related to iron bioavailability when analyzing dietary intake data to determine adequacy of iron intakes. This also suggests that the algorithm employed to estimate FeBIO contributed to the association with Hb. We also found a significant positive association between Hb and FeBIO when the Monsen algorithm was used to estimate FeBIO, which takes into account only the EF of iron absorption, vitamin C, and meat. However, we used the FeBIO estimated by the Bhargava algorithm, because the coefficients were larger than when the Monsen algorithm was used (4.9 vs. 2.2 g/L, respectively, in children aged 12–59 mo).

Previous studies concerning the association between dietary iron and biochemical indicators have found contradictory results. A positive association was found in a study of women in Bangladesh (27), whereas other studies (8,18) found no association. However, one of the latter studies (8) did not take iron bioavailability into account, which may have attenuated the possibility of finding such an association.

We found a negative association with high milk consumption (600 mL), although this was only marginally significant. A previous study found a significant association between consumption of >600 mL cow's milk and anemia in 2-y-old Asian children living in England (33). Our study found a marginal association exclusively in the 24–59-mo age group. It is important to note that only 8% of the children consumed 600 mL cow's milk, which may have limited the possibility to detect such an association.

We fully acknowledge the limitations of the survey design in this analysis. These limitations were largely due to the nature of the study, being a secondary data analysis of a large national survey where it was not feasible to conduct multiple 24-h recalls with the same participants to better describe their usual FeBIO intakes. These limitations are usually present in large-scale national representative dietary surveys; on the other hand, small clinical studies, although accurate, do not allow extrapolating results to the general population and are therefore not as useful for policy making. Anemia can have many causes other than iron deficiency, although in some populations, iron deficiency may be the most important cause. Unfortunately, it is no longer possible to determine serum ferritin concentration in the samples collected in this survey. Despite the limitations mentioned, an association was detected between FeBIO intakes and Hb concentration. It is also pertinent here that a significant association was observed with FeBIO, but not total iron, while controlling for important confounding variables. We think that the main objectives of the article were adequately met with the available data and that valid and pertinent results were derived that can be used for policy making.

The study also has the limitations inherent in the use of the 24-h recall method and of the nutritional composition databases for calculating nutritional intakes, which may lead to imprecision or bias in consumption estimations. The 24-h recall frequently underestimates energy consumption in magnitudes that vary by 2–27% in different populations (48). Nonetheless, if this were the magnitude of the underestimation for FeBIO, this study's basic conclusion concerning insufficient FeBIO consumption would not be altered, given that the estimated intakes of FeBIO were <50% of requirements.

The use of just 1 24-h recall for the dietary study precluded adjustment of the total variance for intrasubject variability, which is generally very high, perhaps representing more than one-half of the total variance. The use of the unadjusted variance does not modify the group estimations of mean FeBIO intake but likely overestimates the range of intakes, because a single day's intake does not reflect usual intake. This may lead to underestimation of the regression coefficients and the magnitude of the association found between FeBIO and Hb may be an underestimate of the real association.

An additional limitation is the unknown body iron reserves of the study population, leading to the use of assumptions of body reserves based on iron-deficiency prevalence rates for the distinct age ranges. Nevertheless, this limitation does not invalidate the conclusion concerning the insufficiency of total and FeBIO in the diet, which was far below the physiological iron needs for the 3 assumed levels of body iron reserves. In addition, this limitation does not alter the conclusions on the association between FeBIO and Hb concentration for children between 12 and 23 mo and for the group as a whole (12–59 mo). For children between 12 and 23 mo, the association between FeBIO and Hb concentration was significant (P < 0.05) for the estimations based on each of the 3 assumed levels of body iron reserves. In contrast, for 24–59-mo-old children, the association was marginally significant for the assumed reserve level of 500 mg (P = 0.058) and not significant for the assumed reserves of 250 mg (P = 0.112) and 0 mg (P = 0.138).

It is also important to note that the algorithm used for estimating FeBIO in the diets of these Mexican children is derived from studies of iron absorption in adults. Nonetheless, use of the algorithm still resulted in a significant association between the estimated FeBIO and Hb in these children, suggesting that the effects of the enhancing and inhibiting factors are similar in adults and children.

Despite the fact that Hb is not a specific indicator of iron status, we found a significant association between FeBIO and Hb in children aged 12–23 mo, an association that was not present between total iron intake and Hb concentration. Given the high cost of direct studies of bioavailability, which restricts their application in population samples, algorithms can be useful for estimating the amount of FeBIO in the diets of populations. Nonetheless, dietary interventions should ultimately be implemented to better quantify the impact of different FeBIO intakes on iron status in populations.

	ACKNOWLEDGMENTS

 
The authors thank Ignacio Méndez for his advice on the statistical methods used and interpretation of results and Simón Barquera and Martha M. Téllez for their comments on a draft of the manuscript.

	FOOTNOTES

 
¹ Supported by funds from the National Institute of Public Health (Mexico).

² Author disclosures: S. C. Rodríguez, C. Hotz, and J. A. Rivera, no conflicts of interest.

⁵ Abbreviations used: EF, enhancing factors of iron absorption; FeBIO, total bioavailable iron; Hb, hemoglobin.

Manuscript received 4 April 2007. Initial review completed 24 April 2007. Revision accepted 3 July 2007.

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TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 

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