A cross-sectional analysis was carried out with data from two public databases combined by child ID. One of the databases contained information from the national survey, Food and nutrition surveillance survey by life stages (FNSS), 2015 (In Spanish: Encuesta de Vigilancia Alimentaria y Nutricional por Etapas de Vida, VIANEV) [18]. The other database included administrative data from public health centers, calledComprehensive Health Insurance (ISHS) Integrated Health Service Systems (ISHS) Health Benefits Report, Ministry of Health 2015 (In Spanish: Reporte de Prestaciones de Salud del Sistema Integrado de Aseguramiento en Salud del Seguro Integral de Salud del Ministerio de Salud, SIASIS) [19]. The data extracted from the ISHS matched the time period of the FNSS (2015) to ensure that the indicators for both datasets were recorded during the same period.

The food and nutritional surveillance survey by stages of life (FNSS)

The FNSS is a nationally representative survey conducted by the National Center for Food and Nutrition, of the National Institute of Health (Spanish: Centro Nacional de Alimentación y Nutrición). The survey used a cluster sample survey design with random selection to represent the national population. The survey looked at nutritional outcomes and food intake in children under 3 years old.

Food intake was measured with a 24-hour food booster over two non-consecutive days. The weight of each food consumed was estimated by weighting an approximately equivalent portion of the food with the survey participant. The dietary information was converted into the amount of nutrients consumed by the child during each day. To estimate the distribution of nutrient intake, the survey used the software, CTÉ PC, developed by Iowa State University [20]. Nutrient intake was compared to dietary recommendations to meet estimated energy requirements (EER) by age and sex, defined by the Department of Nutrition for Health and Development of the World Health Organization. [21,22,23,24]. The calculation determined whether each participant met the nutritional requirements for their age for each nutrient category. The full methodology is described in the final report of the survey [18].

The FNSS survey used a portable spectrophotometer to estimate the hemoglobin concentration of participants. Hemoglobin concentrations have been used to diagnose anemia using cutoffs defined by the World Health Organization. For children aged 6 to 59 months, the survey used the threshold defined by the World Health Organization of less than 11 g per liter [25]. Due to the method of measurement, it is not possible to distinguish between the type or cause of anemia. Iron deficiency anemia is the most common in the population [26].

The FNSS provided information on the water source of the households surveyed. The water source was defined as potable water if it came from a public water source such as public water supplied to the household, a shared water pipe outside the house or a community well [18]. The information is represented in the present study by the categorical variable, access to drinking water, where 0 = no access to a source of drinking water and 1 = the household has access to a source of drinking water.

The FNSS provided information which is used by this study to monitor the effect of household poverty. The variable is not a key predictor of interest, but it is included in the logistic regression analysis to control for its influence. The variable, basic needs met, indicators whether the house meets the basic needs of the family. The house does not meet basic needs if it is built with non-structurally sound materials (plastic, cardboard, etc.), dirt floor, overcrowded, no toilets (indoor or outdoor), a child aged 6 to 12 years old does not go to school, or if the head of the household has not completed primary school.

The FNSS survey database provided the following variables; the child has met the iron recommendations, the child has met the micronutrient recommendations (iron, zinc, vitamin A), the child has met the micronutrient and energy requirements (iron, zinc, vitamin A and calories) , diagnosis of anemia, access to drinking water, basic needs met, sex, age and area of ​​residence (metropolitan, urban or rural Lima).

Comprehensive Health Insurance Integrated Health Service Systems (ISHS)

ISHS is a public database that contains administrative data reported by all public medical centers that accept public health insurance [19]. It provides information on the medical care provided to the population. The database is available on request from the Peruvian Ministry of Health. Diseases reported in the database, which were diagnosed and treated in health centers, were classified according to the International Classification of Diseases: Preparation of Short Lists for Data Tabulation [27]. The information of interest for this study from the ISHS database are cases of intestinal infection or parasitic disease in children in 2016. The information is represented as a binary variable that indicates whether the child has been diagnosed. with infectious intestinal disease (1 = at least 1 infection reported) or if the child was not diagnosed with infectious intestinal disease in a public health center during the year 2015-2016 (0 = no infection reported). The category of “infectious intestinal disease” for this study includes bacterial intestinal infections, viral intestinal infections, and parasitic intestinal infections.

The databases of the FNSS and ISHS surveys were brought together by the Information Technology Department of the Integrated Health Insurance Program, at the request of the authors. The public institution combined the databases of the FNSS and ISHS surveys with the national identification number of the participants. The institution maintains the confidentiality of information and does not share any identifiable information of participants.


Descriptive statistics were analyzed to better understand the experience of anemic children compared to children without anemia. The differences between the two groups were compared with a Chi-square test to identify whether the differences were statistically significant. Two logistical analyzes were conducted to assess the strength of the association between the main predictors and anemia in children in Peru. The first model assessed the association between anemia and intestinal infections, iron intake, a measure of poverty, and gender. The second model evaluated the association between anemia and access to drinking water, iron consumption, a measure of poverty and gender. The model with intestinal supply and the model with access to drinking water are analyzed separately because the intestinal infection mediates between drinking water and anemia, and thus blocks association flow through the causal pathway. [28].

All cases that omitted variables were not included in the analysis. The analysis was adjusted for the sampling plan and the pooling. Analysis was performed with STATA / SE 16.1 [29].

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