Next Article in Journal
Classifying Natural Waters with the Forel-Ule Colour Index System: Results, Applications, Correlations and Crowdsourcing
Next Article in Special Issue
Fat Mass Centile Charts for Brazilian Children and Adolescents and the Identification of the Roles of Socioeconomic Status and Physical Fitness on Fat Mass Development
Previous Article in Journal
A Survey of 42 Semi-Volatile Organic Contaminants in Groundwater along the Grand Canal from Hangzhou to Beijing, East China
Previous Article in Special Issue
Changes in Eating Behaviours among Czech Children and Adolescents from 2002 to 2014 (HBSC Study)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 12
Issue 12
10.3390/ijerph121215045
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Anthropometric Status and Nutritional Intake in Children (6–9 Years) in Valencia (Spain): The ANIVA Study

by
María Morales-Suárez-Varela
1,2,3,*,
Nuria Rubio-López
1,2,3,
Candelaria Ruso
1,
Agustín Llopis-Gonzalez
1,2,3,
Elías Ruiz-Rojo
2,3,4,
Maximino Redondo
5 and
Yolanda Pico
2,6,7
1
Unit of Public Health, Hygiene and Environmental Health, Department of Preventive Medicine and Public Health, Food Science, Toxicology and Legal Medicine, University of Valencia, Valencia 46100, Spain
2
CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
3
Center for Advanced Research in Public Health (CSISP-FISABIO), Valencia 46010, Spain
4
Dirección General de Salud Pública, Conselleria de Sanidad, Valencia 46010, Spain
5
Biochemistry Departament, Agencia Sanitaria Costa del Sol, University of Malaga, Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Marbella 29603, Spain
6
Food and Environmental Safety Research Group, Faculty of Pharmacy, University of Valencia, Valencia 46100, Spain
7
Research Center on Desertification (CIDE, UV-CSIC-GV), Carretera Moncada-Náquera, Moncada 46113, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2015, 12(12), 16082-16095; https://doi.org/10.3390/ijerph121215045
Submission received: 6 October 2015 / Revised: 3 December 2015 / Accepted: 16 December 2015 / Published: 18 December 2015
(This article belongs to the Special Issue Children, Adolescents and Nutrition)
Versions Notes

Abstract

:
The aim of our study was to assess nutritional intake and anthropometric statuses in schoolchildren to subsequently determine nutritional adequacy with Spanish Dietary Reference Intake (DRIs). The ANIVA study, a descriptive cross-sectional study, was conducted in 710 schoolchildren (6–9 years) in 2013–2014 in Valencia (Spain). Children’s dietary intake was measured using 3-day food records, completed by parents. Anthropometric measures (weight and height) were measured according to international standards, and BMI-for-age was calculated and converted into z-scores by WHO-Anthro for age and sex. Nutrient adequacy was assessed using DRI based on estimated average requirement (EAR) or adequate intake (AI). Pearson’s chi-square and Student’s t-test were employed. Of our study group (47.61% boys, 52.39% girls), 53.1% were normoweight and the weight of 46.9% was inadequate; of these, 38.6% had excess body weight (19.6% overweight and 19.0% obesity). We found intakes were lower for biotin, fiber, fluoride, vitamin D (p < 0.016), zinc, iodine, vitamin E, folic acid, calcium and iron (p < 0.017), and higher for lipids, proteins and cholesterol. Our results identify better nutritional adequacy to Spanish recommendations in overweight children. Our findings suggest that nutritional intervention and educational strategies are needed to promote healthy eating in these children and nutritional adequacies.

1. Introduction

Adequate dietary intake is of vital importance for children’s growth and development, not only in physiological terms, but also in mental and behavioral ones [1,2,3]. Hence the importance of early intervention based on acquiring healthy eating habits because they persist in later life [4]. Both excessive and inadequate intake of energy or nutrients may have a detrimental influence on children’s health, and predispose to childhood obesity, dental caries, underachievement at school and lower self-esteem [5,6,7,8], and also to diseases like hypertension, atherosclerosis, obesity, osteoporosis and type 2 diabetes later in life. This means that the prevention of these diseases should start as early on as childhood [2].
Many developed countries are undergoing epidemiological and health transitions with rapid increases in the incidence of overweight, obesity and chronic diseases [9,10,11,12,13,14] across all age groups as a result of changes in dietary and physical activity patterns [13,15,16]. When nutritional intakes are not adjusted to Dietary Reference Intake (DRI), some malnutrition type may exist, as in energy-rich diets and with low intakes of vitamins and minerals, essential nutrients for the organism to adequate function, which affect children’s growth and development [17,18,19].
In the USA, the NHANES study [20] showed that ~30% of American children aged 6–19 years were overweight (≥95th percentile for age) or at risk of being overweight (≥85th percentile, but <95th percentile for age). Overweight rates have almost tripled since the first NHANES study (1971–1974) [20]. According to the 2012 Mexican National Survey of Health and Nutrition [21] 34.4% of Mexican children aged 5–11 years are obese [18]. In Spain, the enKid study [22] found that children aged 6–9 years presented an overweight prevalence of 30.5% (14.5% overweight and 15.9% obesity). The ALADDIN study [23] established that the overweight overall prevalence in children aged 6–9 years was 44.5% (26.2% overweight and 18.3% obesity). This means that one child in every two was overweight.
Usually, childhood is the key step for adopting and consolidating eating habits. This group has been one of the groups most widely influenced by food globalization [18] given the transformation of the current food model with a wider range of industrial food, salty snacks, more soft drinks, skipping breakfast, not eating plenty of fruit, vegetables, grains and drinking milk, and abandoning traditional cuisine [14,18,24]. Thus their nutritionally inadequate diet makes them more vulnerable [25]. In the year 2000, the Krece Plus test assessed the quality of the diet of Spanish children aged 4–14. The results showed that 20% needed to make major adjustments in their diet, and the diet of 51% needed to be sporadically modified. The authors also observed that vitamins A, D, E and B6, and of Ca and Mg were deficient in both genders, while only 25% were considered to benefit from a quality diet [26].
In Spain, children’s growth acts as a sensitive indicator of health status, and its monitoring and evaluation are routine tasks of primary care pediatricians. Thus children who grow well will likely have no relevant associated diseases [27]. At times apparently healthy children with normal height for their age, and even overweight ones, suffer masked malnutrition, which can affect the maximum bone and intellectual development potential [17].
The present study aimed to assess nutritional intake and anthropometric statuses in schoolchildren (6–9 years old) and to subsequently determine nutritional adequacy with Spanish Dietary Reference Intake (DRIs).

2. Samples and Methods

2.1. Participants

The Antropometria y Nutrición Infantil de Valencia (Valencian Anthropometry and Child Nutrition, ANIVA) study is a descriptive cross-sectional study that was conducted in schoolchildren aged 6–9 years who went to one of the eleven participating primary schools. The estimated number of subjects was over 700 according to a simple size calculation based on our preliminary data (Type I error: 0.05, power: 0.8). Children were selected by means of random cluster sampling in schools, and stratified by sex and type of school (i.e., public vs. private). The latter factor was used as an approximate indicator of socio-economic status. Sampling was carried out in two stages: first, schools were selected from lists made available by the Regional Educational Authorities; second, classrooms and pupils were selected.
Data collection took place during academic year 2013–2014. The study was orally presented to the Consejo Escolar (Board of Governors) of each participating school. Following this, a letter was sent to the parents of all the children invited to participate in the study, which outlined the study goals and procedures, and secured their written authorization. The inclusion criteria were: (a) children aged 6–9 years; (b) children who studied primary education at one of the eleven selected schools; (c) parents or legal guardians had to agree about the child participating and give written informed consent. The exclusion criteria were: (a) clinical diagnosis of chronic disease with dietary prescription; (b) absence from school on the days arranged to take body weight and height measures; (c) not properly completing the nutritional record.
The initial sample included 873 children of both genders, of whom 12.8% did not want to participate (N = 112). The subjects who provided incomplete information, improperly completed registration (N = 37) or did not present anthropometric measurements (N = 14) were removed. The participation rate was 81.3% and the resulting final sample comprised 710 children. The study protocol complied with Helsinki Declaration Guidelines and was approved by the Secretaría Autonómica de Educación, Conserjería de Educación, Cultura y Deporte of the Generalitat Valenciana, Valencia, Spain (2014/29630).

2.2. Anthropometric Measurements

During school hours, children’s height and weight were recorded by the same person following standard procedures described by the World Health Organization (WHO) [28], with children standing barefoot in light clothing. All the anthropometric measurements were obtained in duplicate and averaged.
Weight was measured to the nearest 0.05 kg using a calibrated electronic load cell digital scale (OMRON BF511®, Tokyo, Japan) and height was measured with a stadiometer (Seca 213®, Hamburg, Germany). Following the GPC Recommendations of the Spanish Ministry of Health and Social Policy, we took BMI as an index to calibrate nutritional status as it is an easy measure to obtain, is efficient and has been adopted internationally as a reasonable indicator of subcutaneous fat accumulation [29]. With these data, we calculated BMI-for-aged (z-score) with the Anthro software, v.3.2 (WHO, Geneva, Switzerland) [30,31]. Based on the obtained percentile ranking, BMI was used to classify children into one of the following four categories [31]: underweight (≤5th percentile), normoweight (>5th to <85th percentiles), overweight (≥85th to <95th percentiles) or obese (≥95th percentile).

2.3. Examination Protocol and Measurements

Parents were interviewed using a questionnaire to elicit information on their child’s age, sex, medical history, medication, and use of vitamin and mineral supplements. At the same time, we provided parents/guardians details of how to assess the food and drinks consumed by their child. They were asked to record estimated portion sizes for each ingested item. The same training was given to the caregivers responsible for the children while in school dining halls. A visual guide was provided to improve the accuracy of portion size estimates. This was essential to obtain reliable data. Parents were asked to submit food labels with ingredients, brands, added ingredients and the recipes for homemade dishes whenever possible. They were given a telephone number for information and support, which they could call to help resolve any issues that arose while completing the diary.

2.4. Dietary Assessment

To carry out the dietary survey, parents were asked to record all the foods and drinks consumed by their child over a 3-day period, including one non-working day (e.g., Sunday or Saturday) [32,33]. To calculate intakes of calories and macro- and micronutrients of known public health relevance, the researchers inputted data from the food records into an open-source computer software. This program (DIAL®, v2.16) [34], developed by the Department of Nutrition and Dietetics at the Madrid Complutense University, has been previously validated in Spain to assess diets and to manage nutritional data.
This open software includes a list of some of the enriched/fortified foods commonly available in Spain, to which other items can be added. It is possible to add foods to the database and, in this way, we were able to include the nutritional composition of packaged foods taken from food labels.

2.5. Estimate of Nutrient Adequacy/Deficiency

Dietary Reference Intakes (DRIs) [35,36,37] include values for Recommended Dietary Allowances (RDAs), Estimated Average Requirements (EARs), Adequate Intakes (AIs), and Tolerable Upper Intake Levels (ULs), as well as Estimated Energy Requirements (EERs) for energy, and Acceptable Macronutrient Distribution Ranges (AMDRs) for macronutrients. For each nutrient, children were categorized as being at risk of inadequate intake based on whether, or not, they met the corresponding nutritional targets [38] and DRIs [39] proposed for the Spanish population. Comparisons were made with the DRISs used in the USA to explore possible differences. The probability of adequate and usual intake of a given nutrient was calculated as follows: z-score = (estimated nutrient intake—EAR)/SD of EAR [40]. We used EARs for micronutrients, whenever available, and we took the AI values for the nutrients for which EARs were not determined (fiber, fluoride, manganese, potassium and pantothenic acid). The percentage of energy provided by proteins, lipids and carbohydrate was also calculated and compared with AMDRs. Using the data collected on consumed food, we made nutritional assessments of the following intakes: total energy (calories), carbohydrates, lipids, proteins, fiber, thiamine, riboflavin, niacin, pantothenic acid, vitamin B6, biotin, vitamin B12, C, D and E; and also minerals: calcium, phosphorus, magnesium, iron, zinc, iodine, selenium and fluoride. For nutrients presumed harmful (e.g., lipids, cholesterol), the opposite interpretation was applied; diet was considered inadequate if these limits were exceeded, and any intake below them was considered adequate.

2.6. Statistical Analysis

For the anthropometric measures, we compared the four categories (underweight, normoweight (healthy), overweight and obesity) between both genders (girls and boys) with frequency and percentage. We applied Bonferroni corrections to control for multiple comparisons. The EAR or AI cut-point method and the probabilistic approach were used to assess the risk of inadequate nutrient intakes. We ran a Student’s t-test to compare nutritional intakes in children with a different anthropometric status. For the dichotomous categorical variables, we compared the inadequacy of children’s diet to recommended intakes (recommendations met, not at risk vs. not met, at risk) by contingency tables, and using the χ2 test (or Fisher’s exact test, as and when appropriate) to assess statistical significance. The Shapiro-Wilk test was used to confirm assumptions of normality, linearity, homocedasticity and independence. All the p values were two-tailed and statistical significance was set at the conventional cut-off of p < 0.05. Data were entered into an Excel spreadsheet, using double-data entry to minimize the risk of errors, and then transferred to the IBM SPSS version 17.0 software (SPSS Inc., Chicago, IL, USA).

3. Results

3.1. Demographic Characteristics

3.1.1. Children Aged 6–9 Years

The study sample included 710 schoolchildren made up of 372 girls (52.4%) and 338 boys (49.9%). Table 1 includes the characteristics of our sample group according to gender and the four anthropometric categories employed. The study sample’s mean age was 7.95 ± 1.12 years. Girls were heavier than boys, boys were taller, but no statistically significant gender differences were found.
The normoweight prevalence of the study sample was 53.1% (95% CI: 49.35–56.82), and it was higher for girls (53.49%, 95% CI: 48.28–58.65) than for boys (52.66%, 95% CI: 48.28–58.65), but no gender differences were found. Boys showed a higher underweight prevalence of 9.46% (95% CI: 6.56–13.10) vs. 7.25% (95% CI: 4.83–10.38) in girls, and also a higher obesity prevalence of 20.11% (95% CI: 15.97–24.79) vs. 18.01% (95% CI: 14.24–22.30), and a statistically significant difference between gender was observed (p = 0.045). When analyzing height compared to BMI, we observed that underweight boys (129.19 ± 8.41) and normoweight girls (129.39 ± 9.28) were shorter, with statistically significant differences for boys (p < 0.001) and girls (p = 0.004). A growing trend was also noted for height in both genders as the anthropometric category increased.
Table
Table 1. Characteristics of the sample, according to BMI, in the 6–9 years old schoolchildren of both genders.
Table 1. Characteristics of the sample, according to BMI, in the 6–9 years old schoolchildren of both genders.
VariableTotalUnderweightNormoweightOverweightObesity
MeanSDMeanSDMeanSDMeanSDMeanSDp value
Both sexes(n 710)100%(n 59)8.3%(n 377)53.1%(n 139)19.6%(n 135)19.0%
Age (years)7.951.127.881.307.871.148.091.088.060.990.839
Weight (kg)30.957.6529.0911.0427.454.9133.505.9338.926.840.434
Height (cm)130.958.94129.768.68129.348.68132.589.29134.298.240.684
Boys(n 338)100%(n 32 )9.46%(n 178)52.66%(n 60 )17.75%(n 68 )20.11%
Age (years)7.941.087.661.117.791.138.301.018.150.870.002
Weight (kg)30.717.3228.8310.7827.354.5333.735.6137.756.600.001
Height (cm)131.288.47129.198.41129.287.98133.488.96134.637.810.001
Girls(n 372)100%(n 27 )7.25%(n 199)53.49%(n 79)21.23%(n 67 )18.01%
Age (years)7.961.168.141.487.941.147.941.117.971.110.830
Weight (kg)31.167.9529.4011.5327.545.2333.336.1940.106.910.001
Height (cm)130.829.36130.449.18129.399.28131.909.53133.948.710.004
p (boys/girls) weight0.4340.8450.7080.6950.045
p (boys/girls) height0.9880.5870.9020.3220.629
Notes: SD: Standard Deviation; Means with different superscripts were statistically significant at p < 0.05 (Student’s t-test).

3.1.2. Nutritional Characteristics

Table 2 presents nutritional characteristics of the sample according to BMI categories. When we analyzed nutrient intake in boys in accordance with the four anthropometric categories, we observed a statistically significant difference for the intakes of energy, niacin, vitamin D, phosphorus and selenium (p < 0.05). However for girls, no statistically significant differences were found for any type of nutrient intake. When we compared such intakes between boys and girls according to their anthropometric characteristics, we found statistically significant differences for the intakes of energy, carbohydrates, protein, lipids, riboflavin, niacin, vitamin B6, folic acid, calcium, phosphorus, magnesium, iron and selenium (p < 0.05).

3.2. Comparing Nutritional Intake According to DRIs

Table 3 summarizes the proportions of nutritional adequacy in all the children and in the four anthropometric categories. This study indicated intake which in all the children implied: (a) lower than recommended: biotin (inadequate deficit, 98.0%), fiber (inadequate deficit, 97.0%), flouride (inadequate deficit, 92.4%), vitamin D (inadequate deficit, 83.1%), zinc (inadequate deficit, 73.4%), iodine (inadequate deficit, 50.4%), vitamin E (inadequate deficit, 63.5%), folic acid (inadequate deficit, 37.1%), calcium (inadequate deficit, 30.2%), and iron (inadequate deficit, 14.8%); (b) all the children ate more than the recommended quantity of lipids (inadequate excess, 84.9%), proteins (inadequate excess, 66.6%) and cholesterol (inadequate excess, 17.2%).
Table
Table 2. Nutritional characteristics of the sample according to BMI in children aged 6–9 years of both genders.
Table 2. Nutritional characteristics of the sample according to BMI in children aged 6–9 years of both genders.
NutrientBoys (n 338)p ValueGirls (n 372)p Valuep Value Boy/Girl
Underweight (n 32)Normoweight (n 178)Overweight (n 60)Obesity (n 68)Underweight (n 27)Normoweight (n 199)Overweight (n 79)Obesity (n 67)
MeanSDMeanSDMeanSDMeanSDMeanSDMeanSDMeanSDMeanSD
Total energy (kcal/day)1958.81397.792176.76403.812145.47454.292204.24498.640.0491990.93387.492072.61396.742028.49420.931971.45329.220.2680.001
Carbohydrates (g/day)210.1950.11229.4244.07225.3246.40230.5346.460.150201.1943.32214.8745.32207.5949.94209.2436.330.3450.001
Protein (g/day)83.1423.2588.9520.9184.9819.4992.7224.780.10684.0827.2083.2419.0982.2322.5080.4619.010.6970.003
Lipids (g/day)84.5720.8096.2022.5696.6228.2297.1228.840.05790.8423.4894.1623.1292.6822.8487.2821.710.1980.045
Cholesterol (mg/day)287.5077.93325.74106.23321.12103.02336.91111.570.171320.89123.58307.6593.85315.0497.01290.9197.090.4050.079
Fiber (g/day)12.155.5513.9712.4513.337.1815.116.980.55311.835.1712.945.5613.868.3112.485.340.3960.426
Thiamin (mg/day)1.380.481.440.561.420.421.450.470.9211.250.291.370.591.290.361.400.750.4780.396
Riboflavin (mg/day)1.710.441.980.681.980.571.830.480.0531.700.481.770.541.710.521.710.540.7400.001
Niacin (mg/day)30.0810.2336.3211.2734.799.9837.2010.750,00933.5412.3833.189.2033.278.3432.149.030.8480.001
Pantothenic acid (mg/day)5.171.535.601.495.331.535.601.610.3515.411.435.391.335.191.285.341.350.7150.549
Vit. B6 (mg/day)1.810.692.160.822.080.682.080.600.1081.910.701.940.661.920.521.840.740.7580.006
Botin (µg/day)27.279.1328.528.2726.577.2227.278.450.37426.698.2526.758.5126.798.6926.5310.110.9980.563
Vit. B12 (µg/day)5.292.675.973.536.564.716.633.270.2485.173.226.033.895.943.355.702.840.6560.461
Folic acid (µg/day)226.2858.49250.67104.38251.8660.03244.7781.850.530219.7073.79230.4976.00223.7769.47218.1687.280.6520.001
Vit. C (mg/day)96.4542.77105.8954.96113.8252.94108.0455.510.513101.2140.5297.1144.8695.2143.9890.24247.780.6590.074
Vit. A (µg/day)343.03154.78546.45623.14587.78852.04472.17295.090.223420.15299.21480.90630.37399.81233.06413.10297.870.5680.189
Vit. D (µg/day)2.381.453.503.142.761.993.682.740.0462.572.403.132.402.872.062.963.040.6560.080
Vit. E (µg/day)6.661.987.723.187.582.658.433.660.0627.593.007.532.687.972.827.042.430.2290.072
Calcium (mg/day)896.56282.63995.24261.37964.38250.88943.32267.130.147880.04218.35925.14299.44881.51273.81887.61238.730.5580.021
Phosphorus (mg/day)1274.12277.421457.02366.311424.40315.241468.22380.600.0481323.19359.451363.77340.981325.09309.381306.04315.930.5850.001
Magnesium (mg/day)258.5868.82281.5387.99279.9872.73288.1384.850.421256.8567.29270.5769.32262.5768.34248.1558.870.1170.019
Iron (mg/day)11.664.0813.846.1613.404.6413.414.020.17812.124.2812.364.0412.213.8311.944.460.9050.011
Zinc (mg/day)11.5520.999.442.509.091.839.332.230.3648.732.318.711.938.742.288.491.800.8670.105
Iodine (mg/day)84.3921.30104.3661.4294.8225.40120.70157.290.16696.4528.8995.8835.5790.3524.4888.5626.110.2830.032
Selenium (µg/day)96.9036.73114.3338.15109.4932.95126.7841.780.002109.1742.38108.5235.48107.5133.51104.7131.970.8850.002
Fluoride (µg/day)221.22136.27312.38322.44296.11361.80257.82191.740.302266.56248.80271.94248.91307.53291.45297.24317.670.7400.643
Notes: SD: Standard Deviation; Vit.: vitamin; p value < 0.5: was considered statistically significant (Student’s-test).
We identified statistically significant differences between the different anthropometric categories for BMI according to the DRIs in the intakes of carbohydrates (p < 0.049), riboflavin (p < 0.024), vitamin B6 (p < 0.001), vitamin D (p < 0.016) and iron (p < 0.017).
Table
Table 3. Nutritional intake of the sample according to DRI and BMI in children aged ≥6 and <10 years.
Table 3. Nutritional intake of the sample according to DRI and BMI in children aged ≥6 and <10 years.
NutrientDRIsTotal (n 710)Underweight (n 59)Normoweight (n 377)Overweight (n 139)Obesity (n 135)p value
n%n%n%n%n%
Carbohydrates (% TEV)Under DRIs67394.85694.935794.713395.712794.10.049
Met DRIs375.235.1205.364.385.9
Over DRIs0000000000
Protein(% TEV)Under DRIs00000000000.157
Met DRIs23733.41932.213134.75036.03727.4
Over DRIs47366.64067.824665.38964.09872.6
Lipids a (% TEV)Under DRIs152.135.161.610.753.70.174
Met DRIs9213.046.84712.52215.81914.1
Over DRIs60384.95288.132485.911582.711182.2
Cholesterol a (mg/1000 kcal) bUnder DRIs20028.21322.011530.53323.73928.90.691
Met DRIs38854.63661.020153.37956.87253.3
Over DRIs12217.21016.96116.22719.42417.8
Fiber (g/day)Under DRIs68997.05796.636897.613597.112995.60.680
Met DRIs213.023.492.442.964.4
Thiamin (mg/day)Under DRIs425.9711.9225.864.375.20.210
Met DRIs66894.15288.135594.213395.712894.8
Riboflavin (mg/day)Under DRIs557.71016.9225.8139.35107.40.024
Met DRIs65592.34983.135594.212690.6512592.6
Niacin (mg/day)Under DRIs10.111.7000000-
Met DRIs70999.95898.3377100139100135100
Pantothenic acid (mg/day)Under DRIs71.020.511.721.421.5-
Met DRIs70399.037599.55898.313798.613398.5
Vit. B6 (mg/day)Under DRIs10014.11322.05314.11510.8114.10.001
Met DRIs61085.94678.032485.912489.211685.9
Botin (µg/day)Under DRIs142.05898.337198.413697.813096.30.532
Met DRIs69698.011.761.632.253.7
Vit. B12 (µg/day)Under DRIs20.3000010.710.7-
Met DRIs70899.75910037710013899.313499.3
Folic acid (µg/day)Under DRIs26337.12542.413736.34532.45641.50.356
Met DRIs44762.93457.624063.79467.67958.5
Vit. C (mg/day)Under DRIs11516.2915.36316.71812.92518.50.630
Met DRIs59583.85084.731483.312187.111081.5
Vit. A (µg/day)Under DRIs689.6610.2318.21712.21410.40.562
Met DRIs64290.45389.634691.812287.812189.6
Vit. D (µg/day)Under DRIs59183.15491.530280.112589.911081.510.016
Met DRIs11916.958.57519.91410.12518.5
Vit. E (mg/day)Under DRIs45163.54576.323762.98158.39268.10.098
Met DRIs25936.51423.714037.15841.74731.9
Calcium (mg/day)Under DRIs21430.21932.810728.44633.14231.10.710
Met DRIs49569.83967.227071.69366.99368.9
Phosphorus (mg/day)Under DRIs50.711.730.800.010.7-
Met DRIs70599.35898.337499.213910013499.3
Magnesium (mg/day)Under DRIs436.135.1195.1107.2118.30.529
Met DRIs66493.95694.935794.912992.812291.7
Iron (mg/day)Under DRIs10514.81728.85213.81913.71712.20.017
Met DRIs60585.24271.232586.212086.311887.8
Zinc (mg/day)Under DRIs52173.44881.427572.910071.99872.60.542
Met DRIs18926.61118.610227.13928.13727.4
Iodine (µg/day)Under DRIs35850.43457.617546.47553.97351.10.168
Met DRIs35249.62542.420253.66446.16245.9
Selenium (µg/day)Under DRIs0000000000-
Met DRIs71010059100377100139100135100
Fluoride (µg/day)Under DRIs66994.25898.335293.413194.212894.80.493
Met DRIs415.811.7256.685.875.2
Notes: Vit.: vitamin, TEV: total energy value, DRIs: EAR: carbohydrates (50%–60% TEV), proteins (10%–15% TEV), lipids (30%–35% TEV), thiamin (0.8 mg/day), riboflavin (1.2 mg/day), niacin (12 mg/day), vit B6 (1.4 mg/day), biotin (12 µg/day), vit B12 (1.5 µg/day), folic acid (200 µg/day), vit. C (55 mg/day), vit. A (400 µg/day), vit D (5 µg/day), vit E (8 mg/day), calcium (800 mg/day), phosphorus (700 mg/day), iron (9 mg/day), zinc (10 mg/day), iodine (90 µg/day), selenium (30 µg/day) and AI: fiber (25 mg/day), panthothenic acid (3 mg/day), magnesium (180 mg/day), fluoride (1000 µg/day). p value < 0.05: was considered statistically significant (Student’s t-test). a Intakes failed to meet recommendations if they under DRIs, except for total fats and cholesterol, for which inadequate intakes were those over DRIs or nutritional target for Spanish people, respectively. b The DRI for cholesterol was not determinable. Instead the target for the Spanish population of 100 mg/1000 kcal was considered.

4. Discussion

Anthropometry remains one of the most widely used methods for assessing and monitoring health status, nutritional status, as well as child growth in individuals and communities [41]. The present study identified that 53.1% of the population of Valencian schoolchildren was normoweight and 38.6% had excess body weight (19.6% overweight and 19.0% obesity). Being overweight is a worldwide problem that affects developed and developing countries alike. When we compared different Spanish studies conducted in recent decades, we found an alarming growing trend. According to data published in 2006 by the ENSE [42], the prevalence of overweight in children was 21.43% and 15.38% for obesity, as opposed to ENSE published in 2013 [43], with 23.9% overweight and 16.0% obesity. Locally conducted health surveys (the Valencian Community) [44] showed that overweight prevalence was 18.0% overweight and 22.3% for obesity, which means that 4 children in every 10 were overweight or obese, and clearly indicates the progressive increase in the childhood overweight status in our country. This overweight-obesity pattern is similar to that described in other areas in Spain [45,46,47]. European studies have shown a similar percentage of overweight and obesity [48,49,50]. Excess body weight (overweight and obesity) is a multifactorial disorder whose ethiopathogeny implies genetic, metabolic, psychosocial and environmental factors. However, the speed with which their prevalences have increased apparently relates more with environmental factors; e.g., healthy eating habits [51].
Our findings suggest that children aged 6–9 years show scant compliance with the nutritional goals set by the DRIs of the Spanish population [38,39] for biotin, fiber, flouride, vitamin D, zinc, iodine, vitamin E, folic acid, calcium and iron. Excessive lipids, proteins and cholesterol intakes were observed in both sexes. Unexpectedly there were normoweight children who represented the “healthy” category, but did not present proper intakes for their age and gender as they were lower than those recommended. For instance for the normoweight group, a higher micronutrients intake was obtained than in the overweight and obesity categories. It is worth stressing, however, that intake estimates below recommendations did not indicate nutrient deficiencies as recommended intakes far exceeded the mean requirement. However, they are useful for indicating potential deficiencies, which will become greater the larger the differences between those calculated based on real and recommended intakes (DRI). True deficiency statuses should be diagnosed by other means, especially through biochemical analyses [52,53,54].
This study used the nutritional adequacy values from the latest SENC [38] and FESNAD [39] reviews; both institutions assess nutrition in Spain. The values we employed were taken in accordance with age, which we did not separate per gender because the same levels were presented for our study sample’s age group. We found that the DRIs values that covered the nutritional requirements of 50% of the healthy population were the so-called EAR, while the IA are based on the requirements identified experimentally in a healthy population. We used the EAR for carbohydrates, protein, lipids, thiamin, riboflavin, niacin, vitamin B6, biotin, vitamin B12, folic acid, vitamin C, vitamin A, vitamin D, vitamin E, calcium, phosphorus, iron, zinc, iodine and selenium, and the AI parameter for fiber, panthothenic acid, magnesium and fluoride because the EAR for these nutrients have not been determined. We considered this difference in the known reference value when we interpreted the results of nutritional deficiencies.
A diet adequate from a nutritional viewpoint implies a balanced nutritional diet, and that the undesirable quantities of saturated fats, trans-fatty acids or sugars, among others, are minimum, which are related to highly prevalent childhood diseases, such as obesity, hypercholesterolemia or dental caries [52]. Therefore, if child feeding is correct, and if diet nutritional quality is adequate and varied, it will have a direct influence on growth and development.
Energy intake was adequate in most children, and all the anthropometric categories increased, except the obese girls, whose mean intake was similar to that of the underweight category. This might be due to families controlling their eating habits as they are aware that overweight children are at higher risk of becoming obese in adulthood [55]. The observed higher energy intake in boys is consistent with the results of previous studies, which have reported significantly higher energy intake in boys compared to girls. This result was similar to those reported in several Spanish studies [46,47,56]. The intake of carbohydrates and fiber was below that recommended, and this finding coincides with other authors [57,58,59,60,61]. These macronutrients are key nutrients for various body functions, and their low intake may be due children’s general rejection of vegetable and cereals. Of all the schoolchildren we studied, 84.5% presented a lipids intake over the DRIs. The importance of acting with these children stems from the high risk they have of developing degenerative diseases (cardiovascular and obesity) from eating too many lipids, and not just in the short term, but also in adulthood [2,18]. In turn, 17.2% of the schoolchildren presented a value over the DRIs for cholesterol as their intake of monosaccharides and disaccaharides was high [18,62]. Thus reducing their sucrose intake is recommended [1]. Compared with other studies, the total protein intake we observed herein (regardless of it being of animal or plant origin) was lower than in studies done in Poland [2] and Portugal [56]. The high protein intake of our study may be due to most proteins being of animal origin (including proteins from meat, fish, eggs and milk), which can imply early puberty onset in the short term [63] and a long-term risk of diabetes [64].
The mean intakes of all the studied vitamins, except biotin, folic acid, vitamin D and vitamin E, were adequate. The action of biotin and folic acid is relevant because both these micronutrients are inversely related with the plasma homocysteine concentration, which is linked to a higher risk of developing cardiovascular diseases [40]. This is mainly due to children’s general rejection of fish, which could also justify the low vitamin D intake observed herein, with similar values to those found in other studies [52,65]. It should be emphasized that the normoweight category was that with the best mean intake. Low vitamin D intake is clinically associated with adverse health outcomes, including growth retardation, increased risk of autoimmune disease, and delayed dentition or bone deformities through inadequate calcification [66]. Vitamin D is synthesized as a result of exposure to solar ultraviolet-B irradiation [67,68,69], and the climate conditions of the Valencian Community could compensate this shortage. In the same way, vitamin E, n antioxidant present in the basic food items of the Mediterranean diet such as vegetable oils, nuts and green leafy vegetables [70], showed deficient intakes for half the study groups, but higher intakes in the overweight category.
Regarding minerals, even though the majority of the sample reached the DRI for calcium, a small part of the study sample did not. This mineral, which is present in milk, is essential in childhood, and its deficit dietary intake is involved in bone resorption mediated by the parathyroid hormone (PTH), which causes reduced bone mass and osteoporosis in adulthood [58]. Similarly zinc, present in meat, fish, poultry, milk and its by-products, provides 80% of total diet zinc [71]. It was deficient in all the anthropometric categories. This low intake is likely not that important since the whole sample were found to eat protein-rich diets. Finally, iodine values were similar for all the categories, which were all below the DRI, and did not meet 75% of the recommendation. Low iodine intake in children is clinically associated with higher prevalence of thyroid nodular diseases in adulthood [72]. A low iodine intake can be justified by children eating very few marine food items, whose rejection is widespread [73,74].
Suitable anthropometry in a child population is not necessarily a synonym of suitable food intake. Special attention should be paid to the observed nutrient deficiencies, and their intake should be actively reinforced from primary care and schools since such nutrients act directly on child growth and development. Intake of certain foods can be improved by setting up Food Education Programs to encourage healthy eating habits, to promote higher daily intakes of fish, fruit and vegetables, and to eat a decent breakfast. Parents’ education and socio-economic position probably influence children’s eating habits as they either facilitate or restrict understanding nutritional information and fulfilling nutritional recommendations. The school environment, along with family and community environments, are also the most influential educational areas where healthy eating and life style habits are acquired. Attitudes to be taken by schools in terms of nutritional aspects should be intrinsically exemplified to satisfy their educational purpose, and to consequently help avoid excessive body weight (overweight and obesity) in children [51].

Study Limitations

In our child study, the data we had available were insufficient to establish a clear relationship between eating patterns and anthropometric status. Future studies should attempt to clarify this possible relationship. Although the Spanish dietary recommendations for the studied age group (6–9 years) are the same for boys and girls, this could be a weakness. Nor did we have information about arm circumference or triceps skinfold to enable us to know if fat was peripheral or central.
We believe that our study offers strong internal validity given the low attrition rate obtained. We are confident that the self-reported information employed for the nutrition assessment is good quality. Parents and schools were very interested in the study, and were extensively trained and supported to complete food records. They were also followed up over the same period. We understand that these factors compensate for limitations in our generalizability and external validity.

5. Conclusions

Our finding suggests that nutritional intervention and educational strategies are needed in this population of Spanish children to promote healthy eating and to correct inadequacies. Updating Spanish food composition is necessary to ensure reliable precise estimates of nutrient intake. The present study provides a baseline for future intervention programs to prevent children from suffering overweight and obesity problems based on the relevance of acquiring suitable eating habits.

Acknowledgments

We wish to thank all the children and their parents who participated in this study.

Author Contributions

María Morales-Suárez-Varela, Nuria Rubio-López, Agustín Llopis-González and Yolanda Pico had the original idea for the study and, with all co-authors carried out the design. Candela Ruso and Elias Ruiz-Rojo were responsible for recruitment and follow-up of study participants. Maximino Redondo, Nuria Rubio-López and Agustín Llopis-González were responsible for data cleaning and María Morales Suárez-Varela and Yolanda Pico carried out the analyses. María Morales Suárez-Varela, Nuria Rubio-López, Candela Ruso, Agustín Llopis-González, Elias Ruiz-Rojo, Maximino Redondo and Yolanda Pico drafted the manuscript. All authors were involved in preparing the outline of the manuscript, making comments on the manuscript, and approval the final version of the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. FAO/WHO. Diet, Nutrition and the Prevention of Chronic Diseases. 2003. Available online: http://www.who.int/dietphysicalactivity/publications/trs916/en/gsfao_introduction.pdf (accessed on 15 April 2015).
  2. Merkiel, S. Dietary intake in 6-year-old children from southern Poland: Part I—Energy and macronutrient intakes. BMC Pediatr. 2014, 14. [Google Scholar] [CrossRef] [PubMed]
  3. The United Nations Children’s Fund. La Desnutricion Infantil. Causas, Consecuencias y Estrategias Para su Prevencion y Tratamiento. Available online: https://www.unicef.es/sites/www.unicef.es/files/Dossierdesnutricion.pdf (accessed on 17 December 2015).
  4. Gibson, E.L.; Kreichauf, S.; Wildgruber, A.; Vögele, C.; Summerbell, C.D.; Nixon, C.; Moore, H.; Douthwaite, W.; Manios, Y.; ToyBox-Study Group. A narrative review of psychological and educational strategies applied to young children’s eating behaviours aimed at reducing obesity risk. Obes. Rev. 2012, 13, 85–95. [Google Scholar] [CrossRef] [PubMed]
  5. Lobstein, T.; Baur, L.; Uauy, R. Obesity in children and young people: A crisis in public health. Obes. Rev. 2004, 5, 4–85. [Google Scholar] [CrossRef] [PubMed]
  6. Must, A.; Strauss, R.S. Risks and consequences of childhood and adolescent obesity. Int. J. Obes. Relat. Metab. Disord. 1999, 23, 2–11. [Google Scholar] [CrossRef]
  7. McCrindle, B.W. Cardiovascular consequences of childhood obesity. Can. J. Cardiol. 2015, 31, 124–130. [Google Scholar] [CrossRef] [PubMed]
  8. Maunder, E.M.; Nel, J.H.; Steyn, N.P.; Kruger, H.S.; Labadarios, D. Added sugar, macro- and micronutrient intakes and anthropometry of children in a developing world context. PLoS ONE 2015, 10. [Google Scholar] [CrossRef] [Green Version]
  9. Mamun, A.A.; Finlay, J.E. Shifting of undernutrition to overnutrition and its determinants among women of reproductive ages in the 36 low to medium income countries. Obes. Res. Clin. Pract. 2014, 9, 75–86. [Google Scholar] [CrossRef] [PubMed]
  10. Mendez, M.A.; Monteiro, C.A.; Popkin, B.M. Overweight exceeds underweight among women in most developing countries. Am. J. Clin. Nutr. 2005, 81, 714–721. [Google Scholar] [PubMed]
  11. Prentice, A.M. The emerging epidemic of obesity in developing countries. Int. J. Epidemiol. 2006, 35, 93–99. [Google Scholar] [CrossRef] [PubMed]
  12. Ziraba, A.K.; Fotso, J.C.; Ochako, R. Overweight and obesity in urban Africa: A problem of the rich or the poor? BMC Public Health 2009, 9. [Google Scholar] [CrossRef] [PubMed]
  13. Kelishadi, R.; Azizi-Soleiman, F. Controlling childhood obesity: A systematic review on strategies and challenges. J. Res. Med. Sci. 2014, 19, 993–1008. [Google Scholar] [PubMed]
  14. St-Onge, M.P.; Keller, K.L.; Heymsfield, S.B. Changes in childhood food consumption patterns: A cause for concern in light of increasing body weights. Am. J. Clin. Nutr. 2003, 78, 1068–1073. [Google Scholar] [PubMed]
  15. Reilly, J.J.; Methven, E.; McDowell, Z.C.; Hacking, B.; Alexander, D.; Stewart, L.; Kelnar, C.J. Health consequences of obesity. Arch. Dis Child. 2003, 88, 748–752. [Google Scholar] [CrossRef] [PubMed]
  16. Barlow, S.E. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: Summary report. Pediatrics 2007, 120, 164–192. [Google Scholar] [CrossRef] [PubMed]
  17. FAO/WHO. Salud de la Madre, el Recién Nacido, del Niño y del Adolescente. Available online: http://www.who.int/maternal_child_adolescent/topics/child/malnutrition/es/ (accessed on 17 December 2015).
  18. Bogin, B.; Azcorra, H.; Wilson, H.J.; Vázquez-Vázquez, A.; Avila-Escalante, M.L.; Castillo-Burguete, M.T.; Varela-Silva, I.; Dickinson, F. Globalization and children’s diets: The case of Maya of Mexico and Central America. Anthropol. Rev. 2014, 77, 11–32. [Google Scholar] [CrossRef]
  19. Sawaya, A.L.; Martins, P.A.; Baccin-Martins, V.J.; Florêncio, T.T.; Hoffman, D.; do-Carmo, P.; Franco, M.; das-Neves, J. Malnutrition, long-term health and the effect of nutritional recovery. Nestle Nutr. Workshop Ser. Pediatr. Program. 2009, 63, 95–108. [Google Scholar] [PubMed]
  20. Ogden, C.L.; Flegal, K.M.; Carroll, M.D.; Johnson, C.L. Prevalence and trends in overweight among US children and adolescents, 1999–2000. JAMA 2002, 288, 1728–1732. [Google Scholar] [CrossRef] [PubMed]
  21. Instituto Nacional de Salud Pública. Encuesta Nacional de Salud y Nutrición 2012. Available online: http://ensanut.insp.mx/informes/Yucatan-OCT.pdf (accessed on 17 December 2015).
  22. Serra, L.; Ribas, L.; Aranceta, J.; Pérez, C.; Saavedra, P.; Peña, L. Obesidad infantil y juvenil en Espana. Resultados del Estudio enKid (1998–2000). Med. Clin. 2003, 121, 725–732. [Google Scholar] [CrossRef]
  23. Ortega, R.M. Estudio ALADINO. Estudio de Vigilancia del Crecimiento, Alimentación, Actividad Física, Desarrollo Infantil y Obesidad en España, 2011. Available online: http://www.observatorio.naos.aesan.msssi.gob.es/docs/docs/documentos/estudio_ALADINO.pdf (accessed on 17 December 2015).
  24. Miqueleiz, E.; Lostao, L.; Ortega, P.; Santos, J.M.; Astasio, P.; Regidor, E. Socioeconomic pattern in unhealthy diet in children and adolescents in Spain. Aten. Primaria 2014, 46, 433–439. [Google Scholar] [CrossRef] [PubMed]
  25. Ministerio de Sanidad, Servicios Sociales e Igualdad (MSSSI). Estrategia NAOS. 2005. Available online: http://www.naos.aesan.msssi.gob.es/naos/ficheros/estrategia/estrategianaos.pdf (accessed 23 April 2015).
  26. Majem, S.L.; Bartrina, A.J.; Barba, R.L.; Monroy, S.M.; Rodrigo, P.C. Crecimiento y Desarrollo: Dimensión Alimentaria y Nutricional; Masson: Barcelona, Spain, 2003; pp. 45–54. [Google Scholar]
  27. Hernández-Rodríguez, M. El patrón de crecimiento. In Tratado de Endocrinología Pediátrica y de la Adolescencia; Doyma: Barcelona, Spain, 2000. [Google Scholar]
  28. World Health Organization. Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index for Age. 2006. Available online: http://www.who.int/childgrowth/standards/Technical_report.pdf (accessed on 17 December 2015).
  29. Onis, M.; Onyango, A.W.; Borghi, E.; Siyam, A.; Nishida, C.; Siekmann, J. Development of a WHO growth reference for school-aged children and adolescents. Bull. World Health Organ. 2007, 85, 660–667. [Google Scholar] [CrossRef] [PubMed]
  30. World Health Organization. OMS Anthro, a Software for Assessing Growth and Development of the World’s Children (Version 3.2.2). Available online: http://www.who.int/childgrowth/software/es/ (accessed on 20 March 2015).
  31. Centers for Disease Control and Prevention. Defining Childhood Overweight and Obesity. Available online: http://www.cdc.gov/obesity/childhood/defining.html (accessed on 17 December 2015).
  32. Barrett-Connor, E. Nutrition epidemiology: How do we know what they ate? Am. J. Clin. Nutr. 1991, 54, 182–187. [Google Scholar] [CrossRef]
  33. Institute of Medicine (IOM). Dietary Reference Intakes: Applications in Dietary Assessment; National Academy Press: Washington, DC, USA, 2001. [Google Scholar]
  34. Ortega, R.M.; Lopez, A.M.; Andrés, P.; Requejo, A.M.; Aparicio, A.; Molinero, L.M. DIAL Programa Para la Evaluación de Dietas y Gestión de Datos de Alimentación; Alce Ingeniería: Madrid, Spain, 2012. [Google Scholar]
  35. Institute of Medicine (IOM). Dietary Reference Intakes: Applications in Dietary Assessment; National Academy Press: Washington, DC, USA, 2000. [Google Scholar]
  36. Institute of Medicine (IOM). Dietary Reference Intakes: Applications in Dietary Planning; National Academy Press: Washington, DC, USA, 2003. [Google Scholar]
  37. Murphy, S.P.; Barr, S.I. Practice paper of the American Dietetic Association: Using the dietary reference intakes. J. Am. Diet. Assoc. 2011, 111, 762–770. [Google Scholar] [PubMed]
  38. Sociedad Española de Nutrición Comunitaria (SENC). Objetivos nutricionales para la poblacion española. Span. J. Community Nutr. 2001, 17, 178–199. [Google Scholar]
  39. Federación Española de Sociedades de Nutrición; Alimentación y Dietética (FESNAD). Ingestas dietéticas de referencia (IDR) para la población española. Act. Diet. 2010, 14, 196–197. [Google Scholar]
  40. Carriquiry, A.L. Assessing the prevalence of nutrient inadequacy. Public Health Nutr. 1999, 2, 23–33. [Google Scholar] [CrossRef] [PubMed]
  41. Arija, V.; Pérez-Rodrigo, C.; Martínez-de-Vitoria, E.; Ortega, R.M.; Serra-Majem, L.; Ribas, L.; Aranceta, J. Dietary intake and anthropometric reference values in population studies. Nutr. Hosp. 2015, 31, 157–167. [Google Scholar] [PubMed]
  42. Ministerio de Sanidad Servicios Sociales e Igualdad; Instituto Nacional de Estadística. Encuesta Nacional de Salud de España. 2006. Available online: http://www.msssi.gob.es/estadEstudios/estadisticas/encuestaNacional/encuestaIndice2006.htm (accessed on 23 November 2015).
  43. Ministerio de Sanidad Servicios Sociales e Igualdad; Instituto Nacional de Estadística. Encuesta Nacional de Salud de España 2011–2012. Available online: http://www.msssi.gob.es/estadEstudios/estadisticas/encuestaNacional/encuestaNac2011/encuestaResDetall2011.htm (accessed on 27 April 2015).
  44. Generalitat Valenciana. Encuesta de la Salud de la Comunidad Valenciana. 2010. Available online: http://www.san.gva.es/web/sdg-i-d-i/documento-fraccionado-encuesta-salud (accessed on 29 April 2015).
  45. Gulías-González, R.; Martínez-Vizcaíno, V.; García-Prieto, J.C.; Díez-Fernández, A.; Olivas-Bravo, A.; Sánchez-López, M. Excess of weight, but not underweight, is associated with poor physical fitness in children and adolescents from Castilla-La Mancha, Spain. Eur. J. Pediatr. 2014, 173, 727–735. [Google Scholar] [CrossRef] [PubMed]
  46. Rodriguez-Artalejo, F.; Rodrıguez-Artalejo, F.; Garces, C.; Gorgojo, L.; Lopez, E.; Martın-Moreno, J.M.; Benavente, M.; del Barrio, J.L.; Rubio, R.; Ortega, H.; et al. Dietary patterns among children aged 6–7 years in four Spanish cities with widely differing cardiovascular mortality. Eur. J. Clin. Nutr. 2002, 56, 1–8. [Google Scholar] [CrossRef] [PubMed]
  47. Pérez-Farinós, N.; López-Sobaler, A.M.; Dal-Re, M.Á.; Villar, C.; Labrado, E.; Robledo, T.; Ortega, R.M. The ALADINO study: A national study of prevalence of overweight and obesity in Spanish children in 2011. Biomed. Res. Int. 2013, 2013. [Google Scholar] [CrossRef] [PubMed]
  48. Cadenas-Sanchez, C.; Nyström, C.D.; Sanchez-Delgado, G.; Martinez-Tellez, B.; Mora-Gonzalez, J.; Risinger, A.S.; Ruiz, J.R.; Ortega, F.B.; Löf, M. Prevalence of overweight/obesity and fitness level in preschool children from the north compared with the south of Europe: An exploration with two countries. Pediatr. Obes. 2015, 2015. [Google Scholar] [CrossRef] [PubMed]
  49. Maffeis, C.; Tommasi, M.; Tomasselli, F.; Spinelli, J.; Fornari, E.; Scattolo, N.; Marigliano, M.; Morandi, A. Fluid intake and hydration status in obese vs. normal weight children. Eur. J. Clin. Nutr. 2015, 2015. [Google Scholar] [CrossRef] [PubMed]
  50. Smetanina, N.; Albaviciute, E.; Babinska, V.; Karinauskiene, L.; Albertsson-Wikland, K.; Petrauskiene, A.; Verkauskiene, R. Prevalence of overweight/obesity in relation to dietary habits and lifestyle among 7–17 years old children and adolescents in Lithuania. BMC Public Health 2015, 15. [Google Scholar] [CrossRef] [PubMed]
  51. Travé, D.T.; Victoriano, G.F.; Grupo Colaborador de Navarra. Natural evolution of excess body weight (overweight and obesity) in children. An. Pediatr. 2013, 79, 300–306. [Google Scholar]
  52. Serra-Majem, L.; Ribas-Barba, L.; Pérez-Rodrigo, C.; Bartrina, J.A. Nutrient adequacy in Spanish children and adolescents. Br. J. Nutr. 2006, 1, 49–57. [Google Scholar] [CrossRef]
  53. GIBSON. Evaluation of Nutrient Intake Data Principles of Nutritional Assessment 1990.
  54. Henríquez-Sánchez, P.; Díaz-Romero, C.; Rodríguez-Rodríguez, E.; López-Blanco, F.; Alvarez-Leon, E.; Díaz-Cremades, J.; Pastor-Ferrer, M.C.; Serra-Majem, L. Evaluación bioquímica del estado nutricional de la población canaria (1997–1998). Arch. Latinoam. Nutr. 2000, 50, 43–54. [Google Scholar] [PubMed]
  55. Singh, A.S.; Mulder, C.; Twisk, J.W.R.; van-Mechelen, W.; Chinapaw, M.J.M. Tracking of childhood overweight into adulthood: A systematic review of the literature. Obes. Rev. 2008, 9, 474–488. [Google Scholar] [CrossRef] [PubMed]
  56. Moreira, P.; Padez, C.; Mourão, I.; Rosado, V. Dietary calcium and body mass index in Portuguese children. Eur. J. Clin. Nutr. 2005, 59, 861–867. [Google Scholar] [CrossRef] [PubMed]
  57. Ruiz-Roso, B.; Pérez-Olleros, L. Avance de resultados sobre el consumo de fibra en España y beneficios asociados a la ingesta de fibra insoluble. Rev. Esp. Nutr. Comunitaria 2010, 16, 147–153. [Google Scholar] [CrossRef]
  58. Huang, J.Y.; Qi, S.J. Childhood obesity and food intake. World J. Pediatr. 2015, 11, 101–107. [Google Scholar] [CrossRef] [PubMed]
  59. Khan, N.A.; Raine, L.B.; Drollette, E.S.; Scudder, M.R.; Kramer, A.F.; Hillman, C.H. Dietary fiber is positively associated with cognitive control among prepubertal children. J. Nutr. 2015, 145, 143–149. [Google Scholar] [CrossRef] [PubMed]
  60. Kolahdooz, F.; Butler, J.L.; Christiansen, K.; Diette, G.B.; Breysse, P.N.; Hansel, N.N.; McCormack, M.C.; Sheehy, T.; Gittelsohn, J.; Sharma, S. Food and nutrient intake in African American children and adolescents aged 5 to 16 years in Baltimore City. J. Am. Coll. Nutr. 2015, 9, 1–12. [Google Scholar] [CrossRef] [PubMed]
  61. Storey, M.; Anderson, P. Income and race/ethnicity influence dietary fiber intake and vegetable consumption. Nutr. Res. 2014, 34, 844–850. [Google Scholar] [CrossRef] [PubMed]
  62. Niinikoski, H.; Ruottinen, S. Is carbohydrate intake in the first years of life related to future risk of NCDs? Nutr. Metab. Cardiovasc. Dis. 2012, 22, 770–774. [Google Scholar] [CrossRef] [PubMed]
  63. Cheng, G.; Buyken, A.E.; Shi, L.; Karaolis-Danckert, N.; Kroke, A.; Wudy, S.A.; Degen, G.H.; Remer, T. Beyond overweight: Nutrition as an important lifestyle factor influencing timing of puberty. Nutr. Rev. 2012, 70, 133–152. [Google Scholar] [CrossRef] [PubMed]
  64. Sluijs, I.; Beulens, J.W.; van der A, D.L.; Spijkerman, A.M.W.; Grobbee, D.E.; van der Schouw, Y.T. Dietary intake of total, animal, and vegetable protein and risk of type 2 diabetes in the European prospective investigation into cancer and nutrition (EPIC)-NL study. Diabetes Care 2010, 33, 43–48. [Google Scholar] [CrossRef] [PubMed]
  65. Osowski, C.P.; Lindroos, A.K.; Barbieri, H.E.; Becker, W. The contribution of school meals to energy and nutrient intake of Swedish children in relation to dietary guidelines. Food Nutr. Res. 2015, 59. [Google Scholar] [CrossRef]
  66. Zerofsky, M.; Ryder, M.; Bhatia, S.; Stephensen, C.B.; King, J.; Fung, E.B. Effects of early vitamin D deficiency rickets on bone and dental health, growth and immunity. Matern. Child. Nutr. 2015, 2015. [Google Scholar] [CrossRef] [PubMed]
  67. Cutillas-Marco, E.; Fuertes-Prosper, A.; Grant, W.B.; Morales-Suárez-Varela, M.M. Vitamin D deficiency in South Europe: Effect of smoking and aging. Photodermatol. Photoimmunol. Photomed. 2012, 28, 159–161. [Google Scholar] [CrossRef] [PubMed]
  68. Llopis-González, A.; Rubio-López, N.; Pineda-Alonso, M.; Martín-Escudero, J.C.; Chaves, F.J.; Redondo, M.; Morales-Suarez-Varela, M. Hypertension and the fat-soluble vitamins A, D and E. Int. J. Environ. Res. Public Health 2015, 12, 2793–2809. [Google Scholar] [CrossRef] [PubMed]
  69. Grant, W.B.; Holick, M.F. Benefits and requirements of vitamin D for optimal health: A review. Altern. Med. Rev. 2005, 10, 94–111. [Google Scholar] [PubMed]
  70. Kim, Y.N.; Cho, Y.O. Vitamin E status of 20- to 59-year-old adults living in the Seoul metropolitan area of South Korea. Nutr. Res. Pract. 2015, 9, 192–198. [Google Scholar] [CrossRef] [PubMed]
  71. Sandstead, H.H.; Freeland-Graves, J.H. Dietary phytate, zinc and hidden zinc deficiency. J. Trace Elem. Med. Biol. 2014, 28, 414–417. [Google Scholar] [CrossRef] [PubMed]
  72. Vandevijvere, S.; Dramaix, M.; Moreno-Reyes, R. Does a small difference in iodine status among children in two regions of Belgium translate into a different prevalence of thyroid nodular diseases in adults? Eur. J. Nutr. 2012, 51, 477–482. [Google Scholar] [CrossRef] [PubMed]
  73. Campos, R.D.; Barreto, I.D.; Maia, L.R.; Rebouças, S.C.; Cerqueira, T.L.; Oliveira, C.A.; Santos, C.A.; Mendes, C.M.; Teixeira, L.S.; Ramos, H.E. Iodine nutritional status in Brazil: A meta-analysis of all studies performed in the country pinpoints to an insufficient evaluation and heterogeneity. Arch. Endocrinol. MeTable 2015, 59, 13–22. [Google Scholar] [CrossRef] [PubMed]
  74. Katzen-Luchenta, J. The declaration of nutrition, health, and intelligence for the child-to-be. Nutr. Health 2007, 19, 85–102. [Google Scholar] [CrossRef] [PubMed]

Share and Cite

MDPI and ACS Style

Morales-Suárez-Varela, M.; Rubio-López, N.; Ruso, C.; Llopis-Gonzalez, A.; Ruiz-Rojo, E.; Redondo, M.; Pico, Y. Anthropometric Status and Nutritional Intake in Children (6–9 Years) in Valencia (Spain): The ANIVA Study. Int. J. Environ. Res. Public Health 2015, 12, 16082-16095. https://doi.org/10.3390/ijerph121215045

AMA Style

Morales-Suárez-Varela M, Rubio-López N, Ruso C, Llopis-Gonzalez A, Ruiz-Rojo E, Redondo M, Pico Y. Anthropometric Status and Nutritional Intake in Children (6–9 Years) in Valencia (Spain): The ANIVA Study. International Journal of Environmental Research and Public Health. 2015; 12(12):16082-16095. https://doi.org/10.3390/ijerph121215045

Chicago/Turabian Style

Morales-Suárez-Varela, María, Nuria Rubio-López, Candelaria Ruso, Agustín Llopis-Gonzalez, Elías Ruiz-Rojo, Maximino Redondo, and Yolanda Pico. 2015. "Anthropometric Status and Nutritional Intake in Children (6–9 Years) in Valencia (Spain): The ANIVA Study" International Journal of Environmental Research and Public Health 12, no. 12: 16082-16095. https://doi.org/10.3390/ijerph121215045

Article Metrics

Back to TopTop