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Introduction
A child’s physical and emotional development are impacted by their nutritional status; this is especially true for children under the age of five. Healthy nutrition during this formative period impacts a child’s cognitive abilities, height, and prevention of certain diseases1,2,3,4,5. In an effort to promote proper nutrition among children, scientists have released recommendations for children that apply regardless of where they live. Worldwide, child nutrition is a social marker of health since children with better nutritional patterns display better academic performance and better health outcomes. Similarly, the lack of good nutrition - malnutrition - has a negative impact on the development of children. Therefore, it is not surprising that the UN Sustainable Development Goals6 contain goals related to improving childhood nutrition.
Malnutrition refers to the lack of adequate caloric and nutrient intake and can be classified into four types: wasting, stunting, underweight, and mineral and vitamin deficiencies, each of which has a negative impact on child development. Chronic malnutrition, or growth retardation, is the result of extended nutritional deficiencies and tends to be associated with poor socioeconomic factors, inappropriate feeding or care for infants and young children, poor nutritional patterns including nutritional deficiencies, and other maternal health conditions7. Chronic malnutrition has also been shown to have adverse effects on mental and cognitive development of small children, to _impact intellectual performance and capacities, and can cause irreversible damage to brain development8,9,10. Furthermore, chronic malnutrition decreases the body’s immune defenses which can increase the possibility of suffering from various preventable childhood diseases including childhood anemia8,11,12,13. This is especially true for children living in low- and middle-income countries11,12,13,14,15,16,17,18.
Despite efforts to improve childhood nutritional patterns, approximately 155 million children under five years of age suffer from chronic malnutrition, evidenced by stunting, worldwide7. Furthermore, around 45% of childhood deaths under five years of age are related to malnutrition19. This is true in low- and middle-income countries such as Peru7. To combat high chronic malnutrition rates in the country, PERU’s Health Research Priorities for 2019-202320 have made this a priority topic. The purpose of this study was to determine the factors associated with chronic child malnutrition in Peruvian children under 5 years of age using data from the Encuesta Demográfica y de Salud Familiar [Demographic and Family Health Survey] (ENDES) 2018.
Materials and methods
This is a retrospective, cross-sectional analytical study based on secondary sources. The ENDES is a national population survey employing complex probabilistic, stratified, self- weighted and independent sampling broken down by departamentos [states] including both urban and rural areas. The ENDES has been implemented in Peru since 1986 by the National Institute of Statistics and Informatics (INEI) of Peru and provides a large amount of public health data in the country21. In addition, ENDES data are used to systematically monitor compliance with the Sustainable Development Goals (SDGs)22. ENDES databases are freely accessible and can be obtained from the INEI website: / in various formats. The ENDES databases are publicly accessible, and the confidentiality of the participants was taken into account. The present work was approved by the Institute for Research in Biomedical Sciences and the ethics committee of the Faculty of Human Medicine at the Universidad Ricardo Palma. The ENDES 2018 database follows the policy in Peru of “Open Data”24.
The study population consisted of 21,585 children under 5 years of age who met the study criteria. Exclusion criteria for the study included boys and girls older than five years and those younger than five years with incomplete data in the database.
The dependent variable of the study was chronic malnutrition, which is defined as a nutritional condition where the individual is in an inadequate nutritional situation due to lack of necessary nutrients23. Chronic malnutrition was calculated using the WHO child growth standards, differentiating the curves by sex and age groups up to 6 months, 2 years, and 5 years. A dichotomous variable was generated for chronic malnutrition.
The independent variables for the study were the wealth index and the child’s age. The wealth index was calculated based on the assets owned by the parents and was categorized into five quintiles (the first quintile represents the poorest and the fifth the wealthiest). The child’s age was classified into two groups: 0-24 months and 25-60 months. Other variables included sex of the child, type of place of residence (urban, rural), age of the mother by categories, maternal level of education, and participation social programs (glass of milk, popular dining room and Wawa Wasi / Cuna más). Table 1 contains a description of the social programs.
Table 1 Social Programs in Peru
| Vaso de Leche [Glass of Milk]: | A food assistance program created in 1984. Its main objective is food security for vulnerable children aged 0-6 and expectant mothers. The program is administered by the Ministry of Economy and Finance (MEF) in cooperation with and local governments of each province. |
| Comedor Popular [Popular Dinner]: | A program created in 1979. Its main objective is bringing together grassroots organizations and state resources managed through the Food Supplementation Program. The target pop ulation are mothers and women who serve in soup kitchens for the vulnerable population in the area. |
| Wawa Wasi/Cuna Más: | Created in 1999, this social program seeks to provide comprehensive early childhood care through day care for girls and boys under 3 years of age. It is administered by the Ministry of Development and Social Inclusion (MIDIS). |
Source: The ENDES variables used in this study are described at https://proyectos.inei.gob.pe/endes/ 21.
Absolute and relative frequencies were used for the categorical variables and measures of central tendency and dispersion were calculated for the continuous numerical variables. The differences between the groups or associations were estimated via chi-square for the categorical variables and the student’s t test to determine if there was a significant difference between the means of two groups.
Finally, a Poisson regression model with robust variances was estimated, which allowed the calculation of adjusted prevalence ratios (RPa). The accepted statistical significance value in the present study was p <0.05 with 95% confidence intervals. The data were adjusted according to the expansion factor for the weight of the participants.
Results
A total of 21,585 children under 5 years of age were represented in the sample for this study. The average age was 30.43 months (2.5 years), 53% were males, and 78% lived in urban areas. Slightly over a 1/3 of the mothers (35%) were between 21 and 30 years of age. Most of the mothers had a secondary education level (61.29%), and only 33.7% of the children evaluated belonged to a wealthy socioeconomic stratum. The prevalence of chronic malnutrition was 9.7%, varying from 0.9% to 30.1% according to geographic region of residence (Table 2).
Table 2 General characteristics of mothers and chronic malnutrition of children under five years of age, according to ENDES 2018.
| Variable | n (%) |
|---|---|
| Child’s Gender | |
| Male | 11446 (53,0) |
| Female | 10139 (47,0) |
| Child’s Age | |
| 0 to 24 months | 8473 (39,26) |
| 25 to 60 months | 12757 (60,74) |
| Child’s Age* | 30,43 ± 17,04 (Min 1 - Max 59) months |
| Residence | |
| Urban | 16795 (77,8) |
| Rural | 4789 (22,2) |
| Maternal Age | 28,59 ± 9,28 (Min 12 - Max 49) years |
| Maternal Age | |
| 12 to 20 years | 4696 (21,8) |
| 21 to 30 years | 7594 (35,2) |
| 31 to 40 years | 6885 (31,9) |
| 41 to 49 years | 2410 (11,2) |
| Maternal Educacional Level | |
| No Education | 761 (3,5) |
| Elementary | 3999 (18,5) |
| Secondary | 13564 (62,8) |
| Superior (High School) | 3261 (15,1) |
| Wealth Index | |
| Very Poor | 4818 (22,3) |
| Poor | 4934 (22,9) |
| Medium | 4556 (21,1) |
| Wealthy | 3926 (18,2) |
| Very Wealthy | 3350 (15,5) |
| Chronic Malnutrition | |
| Yes | 2097 (9,7) |
| No | 19488 (90,3) |
* Standard Deviation Source: Authors
Underscoring social determinants of health in the health and wellbeing of children, findings from this study suggest that maternal health plays a role in childhood malnutrition. Material age, education, and age of children all play a significant role in malnutrition.
Children with mothers aged 12 to 20 years had a 2.8% higher frequency of malnutrition compared to mothers aged 41 to 49 years (12.1 vs 9.3; p <0.001). Likewise, in mothers without education, their children had 23.9% higher frequency compared to children with mothers with higher education (27 vs 3.1; p <0.001). Chronic malnutrition in families with a very poor wealth index was 20.8% more frequent compared to those with a very rich wealth index (23.5 vs 2.7; p <0.001).
Older children, defined as those between 25 to 60 months, had a 1% higher frequency of having chronic malnutrition compared to those 0 to 24 months (10.1 vs 9.1; p = 0.018). Similarly, children residing in rural areas were 16.2% more likely to experience chronic malnutrition compared to their urban counterparts (22.3 vs 6.1; p <0.001).
The data show that most of the children were not beneficiaries of social programs such as the “Glass of Milk”, “Popular Diner” or “Wawa Wasi / Cuna Más.” In fact, only 2% of study participants benefited from the Popular Diner program (Table 3).
Table 3 Participation in Social programs that include food for children under the age of five
| Social Program | n (%) |
|---|---|
| Glass of Milk* | |
| Yes | 6105 (28,3) |
| No | 15480 (71,7) |
| Popular Diner** | |
| Yes | 477 (2,2) |
| No | 21108 (97,8) |
| Wawa Wasi/Cuna más*** | |
| Yes | 893 (4,1) |
| No | 13988 (64,8) |
| Does not Apply | 6704 (31,1) |
* Managed by the Ministerio de Economia y Finanzas (MEF) ** Managed by the Programa de Complementacion Alimentaria que pertenece at MEF (PAC-MEF) *** Managed by the Ministerio de Desarrollo e Inclusión Social (MIDIS) (https://www.cunamas.gob.pe/) Source: Authors
Participation in social programs-did not seem to insulate children from nutrition related problems. Children enrolled in the Glass of Milk program had a 8.6% higher frequency of malnutrition compared to those who did not participate in the program (15.9 vs 7.3; p <0.001). In the same way, those who were beneficiaries of the Popular Diner program had 9.2% higher frequency of malnutrition compared to those who were not (18.9 vs 9.7; p <0.001) and those who were beneficiaries of Wawa Wasi / Cuna more had 9.2% higher frequency of malnutrition compared to those who did not (18.9 vs 9.7; p <0.001) (Table 4).
Table 4 Bivariate analysis of the characteristics of children under five years of age according to chronic malnutrition, according to 2018.
| Variables | Without chronic malnutrition | With Chronic Malnutrion | valor p | |
|---|---|---|---|---|
| n (%) | n (%) | |||
| Child Sex | 0,458* | |||
| Male | 10317 (90,1) | 1128 (9,9) | ||
| Female | 9171 (90,4) | 969 (9,6) | ||
| Child Age | 0,018* | |||
| 0 to 24 months | 7700 (90,9) | 773 (9,1) | ||
| 25 to 60 months | 11788 (89,9) | 1324 (10,1) | ||
| Child age in months | 30,28 (± 17,19) | 31,84 (± 15,42) | <0,001** | |
| Residence | <0,001* | |||
| Urban | 15767 (93,9) | 1028 (6,1) | ||
| Rural | 3721 (77,7) | 1068 (22,3) | ||
| Maternal age | <0,001* | |||
| 12 to 20 years | 4126 (87,9) | 569 (12,1) | ||
| 21 to 30 years | 6911 (91,0) | 683 (9,0) | ||
| 31 to 40 years | 6264 (90,9) | 621 (9,0) | ||
| 41 to 49 years | 2187 (90,7) | 223 (9,3) | ||
| Matenal Age | 28,70 (± 9,24) | 27,63 (± 9,66) | <0,001** | |
| Maternal Educational level | <0,001* | |||
| No Education | 555 (73,0) | 205 (27,0) | ||
| Primary | 3205 (80,1) | 794 (19,9) | ||
| Secundary | 12567 (92,6) | 997 (7,4) | ||
| Superior | 3161 (96,9) | 100 (3,1) | ||
| Wealth Index | <0,001* | |||
| Very Poor | 3685 (76,5) | 1133 (23,5) | ||
| Poor | 4449 (90,2) | 485 (9,8) | ||
| Medium | 4306 (94,5) | 251 (5,5) | ||
| Wealthy | 3787 (96,4) | 140 (3,6) | ||
| Very Wealthy | 3261 (97,3) | 89 (2,7) | ||
| Vaso de leche | <0,001* | |||
| Yes | 5135 (84,1) | 970 (15,9) | ||
| No | 14353 (92,7) | 1127 (7,3) | ||
| Comedor popular | <0,001* | |||
| Yes | 387 (81,1) | 90 (18,9) | ||
| No | 19101 (90,5) | 2007 (9,7) | ||
| Wawa Wasi/Cuna más | <0,001* | |||
| Yes | 739 (82,8) | 154 (17,2) | ||
| No | 12584 (90,0) | 1404 (10,0) | ||
* Chi square test, significant p value p <0.05 ** Fisher's exact test, significant p-value p <0.05
A multiple regression analysis shows that children aged 25 to 60 months had a 25% higher frequency of having chronic malnutrition compared to those aged 0 to 24 months (PR = 1.25, 95% CI: 1.13 - 1.38). Similarly, children residing in rural areas had a 36% higher frequency compared to those who resided in urban areas (PR = 1.36, 95% CI: 1.21 - 1.54).
Children with mothers aged 41 to 49 years had 11% lower frequency of malnutrition compared to those whose mother were between 12 and 20 years of age (PR = 0.89, 95% CI:77 - 1.04). Likewise, children whose mothers had a higher education, reported a 63% lower frequency of malnutrition compared to children with mothers without education (PR = 0.37, 95% CI: 0.29 - 0.49). Chronic malnutrition in families with a very rich wealth index was 78% less frequent compared to those with a very poor wealth index (OR = 0.22, 95% CI: 0.17 - 0.29). Children who were not beneficiaries of the soup kitchen had a 27% lower frequency compared to those who were beneficiaries (PR = 0.73, 95% CI: 0.58 - 0.91) (Table 5).
Table 5 Bivariate (PR) and multivariate (PRa) analysis of the factors associated with chronic malnutrition in children under five years of age, according to ENDES 2018.
| Variables | Crude | Adjusted* | |||||
|---|---|---|---|---|---|---|---|
| PRc | IC95% | p-value** | Rpa | IC95% | p-value** | ||
| Child Gender | |||||||
| Male | Ref | Ref | |||||
| Female | 0,94 | 0,85 a 1,02 | 0,135 | 0,97 | 0,89 a 1,05 | 0,445 | |
| Child Age | |||||||
| 0 to 24 months | Ref | Ref | |||||
| 25 to 60 months | 1,13 | 1,03 a 1,24 | <0,001 | 1,25 | 1,13 a 1,38 | <0,001 | |
| Residence | |||||||
| Urban | Ref | Ref | |||||
| Rural | 3,57 | 3,27 a 3,89 | <0,001 | 1,36 | 1,21 a 1,54 | <0,001 | |
| Maternal Age | |||||||
| 12 to 20 years | Ref | Ref | |||||
| 21 to 30 years | 0,77 | 0,68 a 0,86 | <0,001 | 0,91 | 0,81 a 1,01 | 0,084 | |
| 31 to 40 years | 0,73 | 0,65 a 0,82 | <0,001 | 0,98 | 0,87 a 1,10 | 0,723 | |
| 41 to 49 years | 0,75 | 0,64 a 0,88 | <0,001 | 0,89 | 0,77 a 1,04 | 0,161 | |
| Maternal Education | |||||||
| No education | Ref | Ref | |||||
| Primary | 0,71 | 0,61 a 0,82 | <0,001 | 0,66 | 0,57 a 0,76 | <0,001 | |
| Secundary | 0,27 | 0,23 a 0,31 | <0,001 | 0,47 | 0,41 a 0,55 | <0,001 | |
| Superior | 0,12 | 0,09 a 0,15 | <0,001 | 0,37 | 0,29 a 0,49 | <0,001 | |
| Wealth Index | |||||||
| Very Poor | Ref | Ref | |||||
| Poor | 0,42 | 0,37 a 0,47 | <0,001 | 0,59 | 0,52 a 0,68 | <0,001 | |
| Medium | 0,25 | 0,21 a 0,29 | <0,001 | 0,39 | 0,33 a 0,47 | <0,001 | |
| Wealthy | 0,15 | 0,12 a 0,18 | <0,001 | 0,26 | 0,21 a 0,33 | <0,001 | |
| Very Wealthy | 0,12 | 0,09 a 0,15 | <0,001 | 0,22 | 0,17 a 0,29 | <0,001 | |
| Glass of Milk | |||||||
| Yes | Ref | Ref | |||||
| No | 0,48 | 0,43 a 0,52 | <0,001 | 0,97 | 0,89 a 1,07 | 0,636 | |
| Popular Diner | |||||||
| Yes | Ref | Ref | |||||
| No | 0,53 | 0,42 a 0,66 | <0,001 | 0,73 | 0,58 a 0,91 | 0,004 | |
| Wawa Wasi/Cuna Más | |||||||
| Yes | Ref | Ref | |||||
| No | 0,58 | 0,48 a 0,68 | <0,001 | 1,01 | 0,86 a 1,19 | 0,863 | |
* Adjusted for all study variables ** significant p value <0.05 RP: prevalence ratio. 95% CI: 95% confidence interval Source: Authors
In an analysis of malnutrition based on geographical location of the Peruvian territory, it was found that: Tacna (0.9%), Moquegua (1.7%), Arequipa (3.65), Ica (3.4%) and Lima (4.5%) had the lowest prevalence values of chronic malnutrition. Conversely, Cajamarca (23.1%) and Huancavelica (30.1%) had the highest prevalence of chronic malnutrition. The Sierra region presented the highest frequencies of malnutrition in the entire country (Figure 1).
Discussion
Results from this study suggest that children living in rural areas had the highest levels of malnutrition in Peru (PRa = 1.36; 95% CI: 1.21 to 1.54, p <0.001). Place of residence, therefore, represents a major risk factor since those areas reported 36% higher rates of chronic malnutrition. Previous studies have yielded conflicting results with some showing rurality playing a role in chronic malnutrition while others did not support those findings26,27,28,29.
The age of the child was a risk factor as it increased the chances of presenting chronic malnutrition by 25%. In our sample, children older than 25 months had higher rates of chronic malnutrition (PRa = 1.25; 95% CI: 1.13 to 1.38, p <0.001). Prior studies support these findings. A study in Ecuador found that chronic malnutrition was more prevalent in children older than 24 months30. A study in Colombia reported that the age of the child increases the risk of chronic malnutrition31. Another study carried out in Mexico in a conflict zone showed that the age of children significantly increases the risk of suffering from chronic malnutrition32
These findings are significant but can be explained since the mean linear growth is restricted from 24 months onwards, after which a zenith or status quo is observed33. Therefore, in children over 24 months, the possibility of showing chronic malnutrition is greater. In the geographic analysis of national chronic malnutrition in Peru, it was found that the highest prevalence of this condition is found in the political region of Huancavelica (30%). While this figure represents a small decrease from findings from a 2016 study25 the figures are still too high. The Huancavelica region is one of the poorest regions of Peru and has one of the lowest wealth indexes in the nation34. This problem is aggravated by the high prevalence of childhood anemia in rural areas and its higher prevalence in the Huancavelica region35. Therefore, these conditions make the Sierra region a vulnerable zone for boys and girls. The higher morbidity and mortality indicates make this region a high priority area for interventions designed to minimize the impact of social determinants of health in the nutritional status of its most vulnerable population segments:its children.
Maternal educational level is one of the most studied determinants of malnutrition. In our study, the majority of mothers with low educational levels had children with higher chronic malnutrition rates. Previous studies in Peru have suggested that illiteracy or incomplete primary education of the mother increases the risk of malnutrition36-37. Similar findings have been reported in other Latin American countries such as Mexico, Colombia, and Brazil38,39,40. Maternal education reflects not only the family’s socioeconomic status, but also is a good predictor of her ability to care for her children36.
While social determinants of health such as low levels of material education and place of residence play a negative role in the nutritional status of children, other socioeconomic factors have a protective impact. In our study, higher educational levels, higher wealth index, and paradoxically not belonging to social safety net programs, resulted in better nutritional status of children. These findings have remained consistent on other studies based on ENDES data (26) with one notable exception based on 2014 ENDES data27.
Conclusión
Although the results of this study suggest a reduction in chronic childhood malnutrition in Peru based on previous studies, opportunities continue exist to completely eliminate this problem in the country. Findings from this study support previous findings indicating that the age of the child, their residence, lack of participation in nutrition programs, and maternal educational level were contributing factors to chronic childhood malnutrition. These results indicate the need to educate mothers about the importance of good nutrition for their children, specifically in breastfeeding children from 0 to 2 years old. These topics could be included in workshops and institutions; thereby allowing greater access of information amongst mothers who attend schools. Community wide educational efforts could be undertaken to reach out of school young mothers.
Data from this study strongly suggest the need for greater outreach and educational programs to-in rural areas and benefit these populations with information and food supplies. There are some limitations that must be considered when evaluating these results. ENDES does not collect information on the nutritional composition of the participants. Future studies should evaluate breastfeeding rates since this variable was not considered in the sample. This single variable could change the nutritional status of children in Peru.
