Clinical trial NCT04915638: Intervention in Children With Malnutrition
Official title: Evaluation of Nutritional Status in Chimalhuacán Children: Anthropometric, Biochemical, and Molecular Approaches
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Overweight and Obesity
Stunted Growth
Malnutrition, Child
Nutrient Deficiency
Keywords: Double burden of malnutrition
Enriched food
Micronutrients
Lead sponsor: Universidad Nacional Autonoma de Mexico
Sponsor class: OTHER
First posted: 2021-06-07
Enrollment: 84
Sex: ALL
Minimum age (years): 8
Maximum age (years): 10
Standard ages: CHILD
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: The intervention consisted of enriched cookies given to children at school for one month. The intervention included two stages. First stage, schoolchildren received placebo cookies (20g of cookies without formula) each day (Monday to Friday) in the morning for 4 weeks. Then, in the second stage, schoolchildren received enriched cookies (20g with a formula FV-UNAM) each day (Monday to Friday) in the morning for 4 weeks. The formula was added to the cookies in a daily dose of 0.33g of organic mix that contained two vitamins, four minerals and omega-3 fatty acids. The exact composition of the formula is a trade secret held by UNAM. Schoolchildren were their own controls because the study was a paired study. In both stages we collected venous blood and anthropometric, blood pressure, and cognitive measurements before the placebo intervention, after 4 weeks from the beginning of formula intervention and post- intervention.
Primary purpose: PREVENTION

Brief summary: Malnutrition is an epidemiologic problem with high prevalence in Mexico. Mexican children present a double burden of malnutrition characterized by the coexistence of undernutrition and micronutrient deficiency alongside excess body weight. Malnutrition is caused by inadequate nutrition, including micronutrients deficiencies, in which children living in rural areas and indigenous populations are disproportionately affected. Malnutrition has been associated with an increased risk of metabolic abnormalities like metabolic syndrome (MS), diabetes, and cardiovascular disease in adulthood. Nutrition-specific interventions are strategies that may reduce or avert malnutrition in children. However, limited intervention studies have been implemented in low-income populations, particularly in rural areas. Therefore, studies that include nutrition-specific intervention with enriched foods aimed at reducing micronutrients deficiencies and that can help in prevention or treatment of metabolic conditions in these populations are still needed. Based on the nutritional characterization carried out in school children in Chimalhuacán, Mexico State, a formula in a powder form was designed for children containing vitamins, minerals, antioxidants, and omega-3 fatty acids that can be used to enrich foods. The present study aimed to evaluate the effect of a 4-week intervention with cookies enriched with a micronutrient formula on the nutritional status in Maya schoolchildren aged 8-10 years. Participants (n=84) were their own control, and the investigators measured, at pre- and post-intervention, anthropometric, clinical, biochemical, and cognitive parameters; diet and molecular parameters were assessed only at pre-intervention. Chi-square test, t-Student paired or Wilcoxon, ANCOVA, and logistic regression were performed to analyze the data.

Detailed description: Mexican children face both forms of malnutrition: under- and overnutrition. Malnutrition is common among children living in rural areas and indigenous populations, where children suffer from food insecurity and cannot access quality nutrition with adequate micronutrients levels. Studies with vulnerable population groups, such as children, in Mexico have shown that micronutrient deficiencies of vitamins A, E, D, C, and minerals like iron, zinc, calcium, and selenium exist. Micronutrient deficiencies can affect physiology functions, growth of children, cognitive function, and impair metabolic processes at biochemical and cellular level. Furthermore, the early exposure of children to malnutrition, in conjunction with the existence of genetic susceptibility, may predispose children to develop metabolic abnormalities like metabolic syndrome (MetS). Thus, increasing the risk of children developing diabetes and cardiovascular diseases in adulthood.

The investigators decided to implement an intervention study in rural communities in the state of Yucatan because this region presents a higher proportion of Maya population than other states of Mexico, but also Yucatan has the highest prevalence of both obesity and undernutrition in children in the country. Previous studies from the investigators group in a Maya child population revealed a frequency of 50% MetS, 34.9% Insulin Resistance (IR), in addition to deficiencies of essential micronutrients. Despite the fact micronutrients are essential for adequate functioning of metabolic processes, few studies in Mexico propose an intervention with enriched food with multiple nutrients such as micronutrients and omega-3 fatty acids. Also, there is little evidence from micronutrient intervention studies in schoolchildren with malnutrition in Mexico, as a strategy to impact on nutritional status and preventive metabolic conditions. For instance, a study by García-López S et al in Mexican schoolchildren with overweight and MetS showed a decrease in lipid and glycemic profiles when supplemented with omega 3-fatty acids for 1 month. Therefore, the present study aimed to evaluate the effect of 4-week intervention with enriched cookies containing a micronutrient formula designed specifically to target the nutritional deficiencies identified in the children. The investigators assessed anthropometric, clinical, biochemical, and cognitive parameters; diet and molecular parameters were assessed only at pre-intervention.

1. Study location: This study was conducted in three elementary schools of Maya rural communities of Yucatan. The communities are Xocén, Tahmek, and San José Oriente.
2. Study design: This study was a paired clinical trial. Participants were their own control for the enriched food intervention.
3. Sample size: The investigators used an equation for finite population. The sample size was estimated to have 80% of statistical power and 95% of a confidence level. A 15% was considered for calculations for dropout during the intervention. Based on the prevalence of malnutrition in Mexico and one community (Xocén), the total number of participants was 106.
4. Sampling procedure: The investigators considered the inclusion and exclusion criterions. Participants were assigned with the convenience sampling technique.
5. Intervention: The intervention consisted of a either a handmade oatmeal cookie or industrialized cookies both enriched with a formula FV-UNAM. The handmade oatmeal cookies enriched with the supplement formula were administered to schoolchildren from Xocén. The industrialized cookies, called Globitos, were donated by DONDÉ cookie factory company, and were supplemented with the same formula as the oatmeal cookies. The enriched Globitos were distributed to the schoolchildren from Tahmek and San José Oriente. The FV formula for children was designed by the Facultad de Química-UNAM. The FV formula is in powder form that contains vitamins, minerals, antioxidants, and omega-3 fatty acids, which are nutrients that have been observed to be deficient in the studied schoolchildren populations. The formulation was within the requirements of the Reference Daily Intake (RDI) for the Mexican population, according to their age, from the Official Mexican Standard (NOM)-051-SCFI/SSA1-2010.
6. Measurements: A nutritional-clinical face-to-face interview was performed with parents or tutors and children. When necessary, assistance from a local translator was used. Nutritional data was collected before pre-intervention. Anthropometric, clinical, biochemical, and cognitive parameters were collected pre- and post-intervention; diet and molecular parameters were assessed only at pre-intervention.

   1. Anthropometric parameters were measured according to the International Society for the Advancement of Kinanthropometry (ISAK). Parameters included were: body weight (SECA 869), height (SECA 217); wrist, arm, and waist circumference (LUFKIN); tricipital skinfold (LANGE); wrist, humerus, and femur diameters (VITRUVIAN). Then, the BMI-for-age and height-for-age indicators were estimated and were translated to z-score according to the World Health Organization (WHO) classification for growth standards. Bone's diameters were translated to z-score and tricipital skinfold to percentile.
   2. Body composition (body fat and fat-free-mass) was determined by bioimpedance analysis (TANITA BC-1500).
   3. Blood pressure was taken twice with a rest period of 10 minutes. The investigators used the average of the two measurements and converted the value to percentile.
   4. Biochemical parameters were collected of peripheral blood samples (8ml) after 12 hours of fasting in the presence of parents or tutors. The 4ml was used for complete blood count and blood chemistry determinations, and also the molecular parameters. The rest of the sample (4ml) will be used for the determination of micronutrients in serum (vitamin A, vitamin E and vitamin D). Blood samples were centrifuged 15 minutes after sample collection and separated into aliquots. Aliquots were kept under optimal conditions (2-8◦C) until processing. All biochemical parameters were determined by the central laboratory of Hospital Juárez de México according to the specific instructions of the manufacturers of the commercial kits. The micronutrients will be quantified by high-efficiency liquid chromatography (HPLC).
   5. Cognitive test was assessed using a Draw-A-Person Intellectual Ability Test for Children, Adolescents and Adults (DAP:IQ), which allows an estimation of intellectual ability. The cognitive test was analyzed by two evaluators.
   6. Dietary intake was assessed using a standard 24-hour diet recall questionnaire at pre-intervention. This assessment consists of face-to-face interviews with parents or tutors, and children. The investigators used household measurements to estimate portion sizes of consumed foods and beverages. Dietary intake data was analyzed by a dietary analysis program (Nutrimind software). This software uses the Mexican Equivalent Food System and U.S. Department of agriculture (USDA) Food database.
   7. Frequency of food intake was estimated using the standard Semi-Quantitative Food Frequency Questionnaire (SFFQ), which was specific for the school age Mexican population. This assessment was a face-to-face interview with children in presence with the teacher. The SFFQ was analyzed using a valid method of Ramírez-Silva I et al., 2016.
   8. Molecular parameters included genotypification of genetic polymorphisms that are associated with metabolic alteration in Mexican adults and Mexico´s indigenous communities. First, the DNA genomic extraction from whole blood was performed using Miller technique. Polymorphisms of genes ATP (Adenosine triphosphate) binding cassette subfamily A member 1 (ABCA1), Peroxisome proliferator activated receptor gamma (PPARG), Glucokinase regulator (GCKR), Cycline-dependent kinase inhibitor-2A/B (CDKN2A/2B), Fat mass and obesity-associated (FTO), and Hepatocyte nuclear factor 4 alpha (HNF4A) were genotyped using TaqMan® probes in Real-time Polymerase Chain Reaction (qPCR) (QS5 from Applied Biosystem). The Hardy-Weinberg (H-W) equilibrium was verified. The allelic frequencies were obtained and were compared to 1000 Genomes Project reported frequencies.
7. Adverse effects of the enriched cookies. Any adverse effects were assessed during a weekly visit. The information was obtained by teachers, parents or tutors.
8. Ethics approval. The study protocol was approved by the Ethics Committee of Hospital Juárez de México (HJM2315/14-C).
9. Data Analysis. Data was analyzed using the Statistical Program for Social Sciences (SPSS), version 20. Descriptive data was shown with tables pre- and post-intervention. Categorical variables were used as percentages. Continuous variables were tested for normality and were presented as mean and standard deviation. To determine significance of observed differences between pre- and post-intervention measurements the investigators used paired t-Student (parametric variables) and Wilcoxon (non-parametric) tests. An ANCOVA was performed to identify correlations between nutritional status and parameters, and was adjusted by age, gender, and BMI-z-score as fixed variables. Logistic regression was used to determine the effects of polymorphism under the risk of metabolic abnormality. A 95% confidence level was used, and a P value \<0.05 was considered statistically significant.

Eligibility criteria: Inclusion Criteria:

* Children with Maya ethnicity confirmed by having parents and grandparents belonging to the same community, and three generations living in the community.
* Children enrolled in 3th and 4th year of elementary school from the same educational center, volunteers, who have the informed consent signed by their parents or tutors, and the assent letter signed by children.
* Aged between 8 to 10 years.
* Both genders.

Exclusion Criteria:

* Any child who does not want to participate in the study.
* Children whose parents or tutors do not agree to sign the informed consent.
* Children who do not sign the assent letter.
* Age less than 8 years and older than 11 years.
* Children using antihypertensive, hypoglycemic or lipid-lowering medications, as well as those that have a history of a condition affected by glucose metabolism, insulin or that alter body composition (cancer, chronic infections, food allergy).
* Under treatment of intake of supplements with vitamins, minerals, antioxidants (\<2 months).
* Children with alcoholism or smoking.

Primary outcomes:
measure: Change of weight from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of height from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of weight-for-age z-score from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of height-for-age z-score from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of Body Mass Index z-score from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of tricipital skinfold percentile from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of bone diameters z-score from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of waist circumference percentile from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of waist-to-height ratio from pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of body fat-mass pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of fat-free-mass pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change in Systolic Blood Pressure pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of red blood count pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of hemoglobin pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of hematocrit pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of platelets pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of white blood cells count in all cell types pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of glucose and lipid profile pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of liver profile pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change of blood proteins pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
measure: Change in cognitive test pre-intervention and after 4 weeks of intervention
timeFrame: Pre-intervention and post-intervention at week 4
Secondary outcomes:
measure: Energy intake
timeFrame: Pre-intervention, assessed up to 1 day
measure: Macronutrients intake in grams
timeFrame: Pre-intervention, assessed up to 1 day
measure: Macronutrients intake in percentage
timeFrame: Pre-intervention, assessed up to 1 day
measure: Micronutrients intake in micrograms
timeFrame: Pre-intervention, assessed up to 1 day
measure: Micronutrients intake in milligrams
timeFrame: Pre-intervention, assessed up to 1 day
measure: Frequency of food intake
timeFrame: Pre-intervention, assessed up to 1 week
measure: Molecular parameters
timeFrame: Pre-intervention, assessed up to 1 day
Other outcomes:
Locations:
city: Mérida
country: Mexico
facility: Facultad de Química, Unidad Académica de la UNAM en Yucatán
state: Yucatán
Study officials:
affiliation: Facultad de Química, UNAM
name: Marta Menjivar, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Popkin BM, Corvalan C, Grummer-Strawn LM. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet. 2020 Jan 4;395(10217):65-74. doi: 10.1016/S0140-6736(19)32497-3. Epub 2019 Dec 15.
citation: Cuevas-Nasu L, Shamah-Levy T, Hernandez-Cordero SL, Gonzalez-Castell LD, Mendez Gomez-Humaran I, Avila-Arcos MA, Rivera-Dommarco JA. [Trends of malnutrition in Mexican children under five years from 1988 to 2016: Analysis of five national surveys]. Salud Publica Mex. 2018 May-Jun;60(3):283-290. doi: 10.21149/8846. Spanish.
citation: Kroker-Lobos MF, Pedroza-Tobias A, Pedraza LS, Rivera JA. The double burden of undernutrition and excess body weight in Mexico. Am J Clin Nutr. 2014 Dec;100(6):1652S-8S. doi: 10.3945/ajcn.114.083832. Epub 2014 Oct 29.
citation: Ramirez-Silva I, Rodriguez-Ramirez S, Barragan-Vazquez S, Castellanos-Gutierrez A, Reyes-Garcia A, Martinez-Pina A, Pedroza-Tobias A. Prevalence of inadequate intake of vitamins and minerals in the Mexican population correcting by nutrient retention factors, Ensanut 2016. Salud Publica Mex. 2020 Sep-Oct;62(5):521-531. doi: 10.21149/11096.
citation: Duggan MB. Prevention of childhood malnutrition: immensity of the challenge and variety of strategies. Paediatr Int Child Health. 2014 Nov;34(4):271-8. doi: 10.1179/2046905514Y.0000000139. Epub 2014 Aug 27.
citation: Tam E, Keats EC, Rind F, Das JK, Bhutta AZA. Micronutrient Supplementation and Fortification Interventions on Health and Development Outcomes among Children Under-Five in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis. Nutrients. 2020 Jan 21;12(2):289. doi: 10.3390/nu12020289.
citation: Martini L, Pecoraro L, Salvottini C, Piacentini G, Atkinson R, Pietrobelli A. Appropriate and inappropriate vitamin supplementation in children. J Nutr Sci. 2020 Jun 5;9:e20. doi: 10.1017/jns.2020.12.
citation: Garcia OP, Ronquillo D, del Carmen Caamano M, Martinez G, Camacho M, Lopez V, Rosado JL. Zinc, iron and vitamins A, C and e are associated with obesity, inflammation, lipid profile and insulin resistance in Mexican school-aged children. Nutrients. 2013 Dec 10;5(12):5012-30. doi: 10.3390/nu5125012.
citation: Wells JC, Sawaya AL, Wibaek R, Mwangome M, Poullas MS, Yajnik CS, Demaio A. The double burden of malnutrition: aetiological pathways and consequences for health. Lancet. 2020 Jan 4;395(10217):75-88. doi: 10.1016/S0140-6736(19)32472-9. Epub 2019 Dec 15.
citation: Garcia-Lopez S, Villanueva Arriaga RE, Najera Medina O, Rodriguez Lopez CP, Figueroa-Valverde L, Cervera EG, Munozcano Skidmore O, Rosas-Nexticapa M. One month of omega-3 fatty acid supplementation improves lipid profiles, glucose levels and blood pressure in overweight schoolchildren with metabolic syndrome. J Pediatr Endocrinol Metab. 2016 Oct 1;29(10):1143-1150. doi: 10.1515/jpem-2015-0324.
citation: de Onis M, Onyango AW, 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 Sep;85(9):660-7. doi: 10.2471/blt.07.043497.
citation: Imuta K, Scarf D, Pharo H, Hayne H. Drawing a close to the use of human figure drawings as a projective measure of intelligence. PLoS One. 2013;8(3):e58991. doi: 10.1371/journal.pone.0058991. Epub 2013 Mar 14.
citation: Ramirez-Silva I, Jimenez-Aguilar A, Valenzuela-Bravo D, Martinez-Tapia B, Rodriguez-Ramirez S, Gaona-Pineda EB, Angulo-Estrada S, Shamah-Levy T. Methodology for estimating dietary data from the semi-quantitative food frequency questionnaire of the Mexican National Health and Nutrition Survey 2012. Salud Publica Mex. 2016 Nov-Dec;58(6):629-638. doi: 10.21149/spm.v58i6.7974.
citation: Lara-Riegos JC, Ortiz-Lopez MG, Pena-Espinoza BI, Montufar-Robles I, Pena-Rico MA, Sanchez-Pozos K, Granados-Silvestre MA, Menjivar M. Diabetes susceptibility in Mayas: Evidence for the involvement of polymorphisms in HHEX, HNF4alpha, KCNJ11, PPARgamma, CDKN2A/2B, SLC30A8, CDC123/CAMK1D, TCF7L2, ABCA1 and SLC16A11 genes. Gene. 2015 Jul 1;565(1):68-75. doi: 10.1016/j.gene.2015.03.065. Epub 2015 Mar 31.
citation: Moreno-Estrada A, Gignoux CR, Fernandez-Lopez JC, Zakharia F, Sikora M, Contreras AV, Acuna-Alonzo V, Sandoval K, Eng C, Romero-Hidalgo S, Ortiz-Tello P, Robles V, Kenny EE, Nuno-Arana I, Barquera-Lozano R, Macin-Perez G, Granados-Arriola J, Huntsman S, Galanter JM, Via M, Ford JG, Chapela R, Rodriguez-Cintron W, Rodriguez-Santana JR, Romieu I, Sienra-Monge JJ, del Rio Navarro B, London SJ, Ruiz-Linares A, Garcia-Herrera R, Estrada K, Hidalgo-Miranda A, Jimenez-Sanchez G, Carnevale A, Soberon X, Canizales-Quinteros S, Rangel-Villalobos H, Silva-Zolezzi I, Burchard EG, Bustamante CD. Human genetics. The genetics of Mexico recapitulates Native American substructure and affects biomedical traits. Science. 2014 Jun 13;344(6189):1280-5. doi: 10.1126/science.1251688. Epub 2014 Jun 12.
citation: Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988 Feb 11;16(3):1215. doi: 10.1093/nar/16.3.1215. No abstract available.
citation: Ashwell M, Hsieh SD. Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr. 2005 Aug;56(5):303-7. doi: 10.1080/09637480500195066.
citation: de Ferranti SD, Gauvreau K, Ludwig DS, Neufeld EJ, Newburger JW, Rifai N. Prevalence of the metabolic syndrome in American adolescents: findings from the Third National Health and Nutrition Examination Survey. Circulation. 2004 Oct 19;110(16):2494-7. doi: 10.1161/01.CIR.0000145117.40114.C7. Epub 2004 Oct 11.
citation: Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents; National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011 Dec;128 Suppl 5(Suppl 5):S213-56. doi: 10.1542/peds.2009-2107C. Epub 2011 Nov 14. No abstract available.
citation: Mendez N, Barrera-Perez TL, Palma-Solis M, Zavala-Castro J, Dickinson F, Azcorra H, Prelip M. ETHNICITY AND INCOME IMPACT ON BMI AND STATURE OF SCHOOL CHILDREN LIVING IN URBAN SOUTHERN MEXICO. J Biosoc Sci. 2016 Mar;48(2):143-57. doi: 10.1017/S0021932015000127. Epub 2015 Jun 4.
citation: 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: Methods and development. [Website]. 2006. Retrieved from http://www.who.int/childgrowth/standards/en/
citation: Shamah-Levy T, Vielma-Orozco E, Heredia-Hernández O, Romero-Martínez M, Mojica-Cuevas J, Cuevas-Nasu L, Santaella-Castell JA R-DJE. Encuesta Nacional de Salud y Nutrición 2018-19: Resultados Nacionales. Cuernavaca,. Instituto Nacional de Salud Pública. 2020. 1689-1699 p.
citation: Stewart A, Marfell-Jones M, Olds T, Ridder H. International standards for anthropometric assessment. Lower Hutt, New Zealand: International Society for the Advancement of Kinanthropometry - ISAK, 2011.