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Ciência & Saúde Coletiva

Print version ISSN 1413-8123On-line version ISSN 1678-4561

Ciênc. saúde coletiva vol.25 no.7 Rio de Janeiro July 2020  Epub July 08, 2020

http://dx.doi.org/10.1590/1413-81232020257.21482018 

ARTICLE

Malnutrition and associated factors among quilombola children under 60 months of age in two cities of the state of Maranhão, Brazil

Victor Nogueira da Cruz Silveira1 
http://orcid.org/0000-0002-5271-7412

Luana Lopes Padilha2 
http://orcid.org/0000-0002-7162-2726

Maria Tereza Borges Araújo Frota1 
http://orcid.org/0000-0001-6889-5785

1Departamento de Ciências Fisiológicas, Universidade Federal do Maranhão (UFMA). Av. Portugueses, Vila Bacanga. 65080-805 São Luís MA Brasil. victorncsilveira@gmail.com

2Programa de Pós-Graduação em Saúde Coletiva, Departamento de Saúde Pública, UFMA. São Luís MA Brasil.


Abstract

Objective: To evaluate the prevalence of malnutrition in children under 60 months of age living in quilombo remnant communities of two municipalities in the state of Maranhão and their associated factors. Methods: This is a cross-sectional study conducted with a sample of 372 children in August 2015. Socioeconomic, demographic, maternal and child information were collected. The anthropometry followed the one proposed by the World Health Organization. Height-for-age and weight-for-height rates were calculated using Anthro software version 3.2.2. Poisson regression was performed with a robust variance for the association of malnutrition with the studied variables, using Stata software version 14.0. Results: Child malnutrition was high for height-for-age (15.1%) and weight-for-height (7%). Children whose mothers had a short height (< 1.497 m) were more likely to have height-for-age deficits (p < 0.05). No variables were statistically associated with low weight-for-height. Conclusion: Child malnutrition persists as a public health problem in vulnerable regions, and maternal factors such as low maternal height may explain the short stature of the children. The need for actions to address this nutritional deviation is pointed out.

Key words Preschoolers; Child malnutrition; Black people

Resumo

O objetivo deste artigo é avaliar a prevalência de desnutrição em crianças menores de 60 meses residentes em comunidades remanescentes de quilombos de dois municípios do estado do Maranhão e seus fatores associados. Estudo transversal com amostra de 372 crianças realizado em agosto de 2015. Foram coletadas informações socioeconômicas, demográficas, maternas e das crianças. A antropometria seguiu o proposto pela Organização Mundial da Saúde. Foram calculados os índices estatura para idade e peso para estatura utilizando o software Anthro versão 3.2.2. Foi realizada regressão de Poisson com variância robusta para a associação da desnutrição com as variáveis estudadas, utilizando o software Stata versão 14.0. A desnutrição em crianças foi elevada segundo a estatura-por-idade (15,1%) e peso-para-estatura (7%). Crianças cujas mães possuíam baixa estatura (< 1,497 m) apresentaram mais chances de possuírem déficit de estatura-para-idade (p < 0,05). Nenhuma variável se associou estatisticamente ao baixo peso-para-estatura. A desnutrição infantil persiste como problema de saúde pública em regiões vulneráveis e os fatores maternos como a baixa estatura materna podem explicar a baixa estatura dos filhos. Aponta-se para a necessidade de ações de enfrentamento deste desvio nutricional.

Palavras-chave Pré-escolares; Desnutrição infantil; População negra

Introduction

The Brazilian black population comprises 8.9% of the population of Brazil and is grouped, especially in the Northeast (11%) and Southeast (9.7%)1. A significant part of this population is concentrated in the poorest strata of the country, as a result of social inequities to which the black race has historically been subjected since the slavery period2,3.

Within the general black population, there is an African Brazilian social group that descends from Africans slaves and lives in isolated rural areas, which in the enslaved period existed as a symbol of resistance and which maintains strong ties with black African culture, namely, the quilombos3. After the end of the slave-holding period, these communities were renamed quilombo remnant communities2.

One of the poorest states in the country, Maranhão concentrates the most significant proportion of black residents (74%)1 and quilombo remnant communities4. Because they serve as a refuge, they are isolated, with poor infrastructure and difficult access to essential services such as health and education5,6.

Due to the consequences of quilombola ancestry, black people have an unequal insertion in the labor market, usually using informal occupations and, consequently, with lower incomes. When compared to white and yellow, blacks earn an average of 1.8 times less7, which reflects on their health and nutrition conditions, especially in more vulnerable segments such as women and children under 60 months.

Among the most significant nutritional deviations in these vulnerable segments is malnutrition. Childhood malnutrition results from the interaction of multiple factors, and their consequences extrapolate adequate growth and development, affecting neurological development and, in extreme cases, result in the early death of the child5,6. Malnutrition is responsible for 30% of the deaths of children under 60 months, reaching 50% in developing countries8.

In Brazil, the malnutrition rate ranks ninth among the causes of infant mortality and is one of the leading causes of death in all the states of the North and Northeast9. In parallel to this scenario, being black is the second major cause of infant death, when based on mortality by color or race10.

Research on the nutritional status of children is scarce in the quilombo remnant communities. Studies to date have found a prevalence of malnutrition ranging from 9.7% in quilombo remnant communities in the State of Alagoas5 to 31.1% in communities in the state of Pará6, showing that child malnutrition still figures as one of the essential nutritional problems in quilombola communities.

Thus, considering the relevance of research of this nature, coupled with the fact that knowing this nutritional scenario of quilombola children can give subsidy for the development of actions and strategies aimed at feeding and nutrition of these communities, this study aims to evaluate the prevalence of malnutrition in children under 60 months of age living in quilombo remnant communities of two municipalities in the state of Maranhão and their associated factors.

Methods

This is a cross-sectional study integrated with the study “Conditions of Nutrition and Food Safety of Women and Children of Quilombola Communities in Maranhão”, developed with the aim of evaluating the health and nutrition conditions of children under five in quilombola communities in Maranhão and, besides nutritional status, evaluated socioeconomic and demographic aspects, family food insecurity and the anemia status of women and children.

The research was carried out in quilombo remnant communities of the municipalities of Penalva and Viana, Maranhão State, with or without a collective land tenure certificate issued by official bodies. We visited all households in which at least one child under 60 months lived in 27 communities located in the rural area of the mentioned municipalities.

Municipalities were selected by convenience because they were communities where local leaders were receptive to the study. The sample was of the probabilistic type, calculated with a confidence level of 95% and a sampling error of 5%, with reference the percentage of children with malnutrition in the Northeast region of 5.9%11 and adding 20% for eventual losses, totalizing 152 individuals.

The study sample consisted of 373 children under 60 months of age, accompanied by the mother or responsible in reproductive age. In this study, one child who refused to participate was excluded, making up a total sample of 372 children. In the case of two or more children in the same household within the age range of the study, the youngest child was chosen. The criteria for non-inclusion were twin children and those with sickle cell anemia.

Data collection took place in August 2015, after previous contacts with local leaders to request consent and collaboration to carry out the research. Upon reaching the municipality, these leaders intermediated the contact with the Community Health Workers (ACS) of the Family Health Strategy (ESF). From then on, we elaborated the daily scripts in each community, the identification of the families with the desired profile and the orientation of the teams to visit the homes, always accompanied by the ACS responsible for that micro-area and a local community leader.

The Informed Consent Form was signed after the participant agreed to respond to the form. The original copy was retained by the interviewer and a copy was held at the household visited for safekeeping by the respondent. The respondents who were unable to sign their name placed their fingerprint at the signature site.

The interviews were carried out at the child’s household through an adapted, validated and pre-codified form12, applied with priority to the biological mother and, in her absence thereof, with the legal guardian or caregiver of the child, provided that she lived in the same household, met the age prerequisite and could provide the requested information.

At the same time, anthropometric measures were taken according to WHO recommendations (2006)13. The children’s weight was gauged using the Omron® brand (Omron Healthcare Inc. U.S.A.), HBF 214 model, with a 150 kg capacity and 100 g scales. Children under two years of age were weighed together with the mother with a subsequent weight reduction calculation13.

The length of children under two years of age was measured in a horizontal position by the infantometer Sanny® brand, with 100 cm breadth. The height of children older than two years was gauged by the Alturexata® anthropometer, ranging from 0 to 2.13 m and subdivisions of 0.1 cm. All subjects were weighed and measured without shoes, wearing only light clothing. Two measurements of weight and height were assessed and recorded on the form. The mean of each measurement was used for the analysis. The interviewers worked in pairs in the anthropometric measurements. New measurements were taken when the two measures of weight differed by more than 100 g and those of height by more than 1.0 cm13.

The children were evaluated according to the anthropometric indices weight-for-height (W/H) and height-for-age (H/A) calculated in Z score using the software Anthro version 3.2.214 based on the current population of reference13. Cut-off points for nutritional status assessment were established according to the WHO (2006)13.

At the end of each workday, the interviewers checked and coded the forms, which were reviewed by the field supervisor, in order to detect fill-in gaps that required an immediate return to the previously visited household. Then the interview control worksheet was filled out to evaluate the coverage of the target for that location and the forms were filed and kept.

After interviewing and collecting the nutritional data, the field team guided the families of the individuals studied regarding adequate and healthy diet. Participants who evidenced a nutritional risk or a positive result for anemia were referred to the Primary Healthcare Facility of that micro-area.

Data were double-entered in the Epi-info program, version 3.5.2, in order to identify entry inconsistencies. For the analysis of the data, the program STATA®, version 14.0 was used. Factors associated with children malnutrition were identified in two stages. In the bivariate analysis, the simple Poisson regression was used to identify the independent variables that showed associations with the nutritional deficits (p < 0.20) that were selected to compose the multiple models. In the second step, the factors associated with height-for-age and weight-for-height were identified using a multiple, hierarchical analysis Poisson regression (robust standard error) using an adapted conceptual model15 (Figure 1):

Adapted from Souza et al.15.

Figure 1 Conceptual model with hierarchical selection for the determination of malnutrition in children under 60 months. 

- Block 1 - Socioeconomic and demographic factors: gender of the child and head of the household, child’s age, schooling and labor relationship of the head of the household, household income, total number of people residing in the household, participation in the Family Grant Program and the Economic Classification Criteria Brazil;

- Block 2 - Access to services and housing conditions: Sanitary sewage, waste disposal, origin and treatment of water;

- Block 3 - Maternal factors: age, total and exclusive breastfeeding, height and BMI;

- Block 4 - Healthcare and nutrition: Visit of the community health worker and coverage of the Family Health Strategy;

- Block 5 - Birth characteristics: Birth weight;

- Block 6 - Child morbidities: Diarrhea, cough and fever in the last two weeks

We started the analysis of the multiple model from the distal to the proximal block. The variables with a p-value < 0.20 by Poisson regression with robust variance were selected as a factor associated with nutritional deficits and remained in the multiple models in subsequent block analyses. In the final model, the one with a p-value < 0.05 was considered as a statistically significant variable after all the adjustments.

The Research Ethics Committee of the Federal University of Maranhão approved the project under Opinion Nº 1.627.919 as per the requirements of the Resolution CNS 466/12 of the National Health Council and its amendments.

Results

The mean age of the children studied was 23.1 ± 15.7 months. All the characteristics evaluated are described in Tables 1 and 2. The prevalence of H/A deficit was 15.1% (95% CI: 11.4-18.7) and of W/H deficit was 7.0 % (95% CI: 4.4-9.6).

Table 1 Distribution of quilombola children under five years of age by socioeconomic and demographic conditions, access to services and housing and health conditions. Maranhão, 2015. 

Variables/categories n %
Child's gender
Male 182 48.92
Female 190 51.08
Head of the household's gender
Male 180 48.39
Female 192 51.61
Head of household's schooling
0 - 4 years 191 51.34
> 4 years 160 43.01
No information 21 5.65
Head of household's work relationship
Not working 74 19.89
Retired 15 4.03
Informal 242 65.05
Formal 40 10.75
No information 01 0.27
Household income
< 1 minimum wage 266 71.51
≥ 1 minimum wage 102 27.42
No information 04 1.08
Family Grant Program
Yes 307 85.53
No 07 1.88
No information 58 15.59
Brazil's Economic Classification Criteria
Class C 32 8.60
Class D 171 45.97
Class E 148 39.78
No information 21 5.65
Sanitary sewage
Public network / Septic tank 42 11.35
Rudimentary cesspit / Ditch / Open-air 328 88.65
No information 02 0.54
Water origin
Public network 18 4.84
Well / Water-hole / Claypit / Water truck 354 95.16
Water treatment
With treatment 178 47.85
Filtered or without treatment 194 52.15
Total number of people living at home
1 - 5 people 242 65.05
6 or more people 130 34.95
Waste disposal
Urban collection 01 0.27
Burned / Buried 347 93.28
Open-air dumping 24 6.45
Total 372 100.00

Table 2 Distribution of quilombola children under five years of age by maternal factors and child morbidity. Maranhão, 2015. 

Variables / categories N %
Maternal age
> 19 years 319 85.75
≤ 19 years 53 14.25
Self-referred maternal skin color
White 16 4.30
Brown / Black 354 95.16
No information 02 0.54
Maternal height (n=248)
1º (1.415 - 1.497m) 127 34.14
2º (1.497 - 1.533m) 121 32.53
3º (1.533 - 1.67m) 124 33.33
Maternal BMI
Underweight 20 5.38
Eutrophy 191 51.34
Overweight 83 22.31
Obesity 49 13.17
No information* 29 7.80
Family Health Strategy
Yes 60 16.13
No 309 83.06
No information 03 0.81
Community Health Worker's visit
Yes 334 89.78
No 38 10.22
Total breastfeeding
Yes 365 98.12
No 06 1.61
No information 01 0.27
Exclusive breastfeeding
Did not receive food before 6 months 228 61.29
Received food before 6 months 115 30.91
No information 29 7.80
Birth weight (n = 317)
< 2500 g 36 9.68
≥ 2500 g 281 75.54
No information 55 14.78
Diarrhea in the last two weeks
Yes 327 87.90
No 45 12.10
Cough
Yes 190 51.08
No 182 48.92
Total 372 100.00

Table 3 shows the bivariate analyzes that associated with the H/A deficit. The variables associated with the outcome were: the child’s age, gender of the head of the household and the social class of the socioeconomic and demographic block, the sanitary sewage of the block of access to services and housing conditions, the tertile of the maternal height of the block of maternal factors, birth weight of the birth characteristics and presence of diarrhea and fever in the last two weeks of the infant’s morbidities block (p < 0.20).

The variables associated in the bivariate analysis were submitted to a multiple and hierarchical analysis of the H/A deficit. The maternal height tertile was the only factor associated with this outcome (PR: 4.08, 95% CI: 1.95-8.52; p < 0.001), showing that the deficit of this rate was more prevalent in the children of women with height below 1,497 m (Table 3).

Table 3 Prevalence (%) and crude and adjusted prevalence ratios (PR) of height deficit in children under 60 months by socioeconomic and demographic factors, access to services and housing conditions, maternal factors, birth characteristics and morbidity of children. Maranhão, 2015. 

Variables / categories Height-for-age deficit
% Crude PR p Adjusted PR p
Socioeconomic and demographic factors
Child's gender
Male 50.0 0.95 0.844
Female 50.0 1
Child's age
< 24 months 51.8 0.68 0.111 0.65 0.080
≥ 24 months 48.2 1 1
Head of the household's gender
Male
Female
39.3
60.7
1
1.44
0.150
1
1.35
0.276
Household income
<1 minimum wage 73.2 1.05 0.866
≥1 minimum wage 26.8 1
Social Class
Class C 1.9 0.16 0.071 0.20 0.115
Class D 45.3 0.73 0.231 0.66 0.101
Class E 52.8 1 1
Maternal schooling
0-4 years 41.1 0.74 0.235
> 4 years 58.9 1
Access to services and housing conditions
Sanitary sewage
Public network/Septic tank 3.6 1 0.077 1
Rudimentary cesspit/Ditch 96.4 3.46 2.49 0.201
Water supply
Public network 3.6 1 0.638
Well/water-hole/clay pit/water truck 96.4 1.37
Drinking water treatment
Treated 41.1 1 0.265
Filtered or untreated 58.9 1.37
Total number of people in the residence
1-5 people 60.7 1 0.432
6 or more people 39.3 1.22
Maternal factors
Maternal age
≤ 19 years 8.9 0.59 0.217
> 19 years 91.1 1
Maternal height (tertile)
1º (1.415 - 1.497m)
2º (1.497 - 1.533m)
60.7
25.1
4.18
1.78
<0.001
4.08
1.73
<0.001
3º (1.533 - 1.67m) 14.3 1 1
Maternal BMI
Underweight 7.8 2.45 0.418
Eutrophy 54.9 1.80
Overweight 29.4 2.21
Obesity 7.8 1
Healthcare and nutrition
Family Health Strategy - ESF
Yes 16.1 1 0.985
No 83.9 1.00
Community Health Worker's visit
Yes 92.9 1 0.410
No 7.1 0.68
Breastfeeding
Yes 98.2 1 0.898
No 1.8 1.13
Exclusive breastfeeding
Yes 66.7 1 0.974
No 33.3 1.00
Characteristics of birth
Birth weight
< 2500 g
≥ 2500 g
18.2
81.8
1.74
1
0.124
0.94
1
0.937
Child's morbidity
Diarrhea in the last two weeks
Yes
No
17.9
82.1
1.58
1
0.151 1.49
1
0.193
Cough in the last two weeks
Yes 46.4 0.92 0.717
No 51 1
Fever in the last two weeks
Yes 46.2 1.72 0.130 1.42 0.396
No 53.8 1 1

Table 4 shows the bivariate analyses that were associated with the W/H deficit, namely: the age of the child of the socioeconomic and demographic block; and the tertile of maternal height and BMI of the maternal factors block (p < 0.20). No variables were associated with this outcome in the multiple analysis (p > 0.05).

Table 4 Prevalence (%) and crude and adjusted prevalence ratios (PR) of the weight-for-height deficit in children under 60 months by socioeconomic and demographic factors, access to services and housing conditions, maternal factors, birth characteristics and morbidity of children. Maranhão, 2015. 

Variables / categories Weight-for-height deficit
% Crude PR p Adjusted PR p
Socioeconomic and demographic factors
Child's gender
Male 53.9 0.81 0.594
Female 46.1 1
Child's age
< 24 months 23.1 1 1
≥ 24 months 76.9 2.41 0.052 2.34 0.090
Head of the household's gender
Male
Female
50
50
1
0.93

0.853
Household income
<1 minimum wage 76.9 1.28 0.581
≥1 minimum wage 23.1 1
Social Class
Class C 3.8 0.35 0.308
Class D 46.2 0.79 0.548
Class E 50 1
Maternal schooling
≤ 4 years 53.8 0.91 0.825
> 4 years 46.2 1
Access to services and housing conditions
Sanitary sewage
Public network/Septic tank 3.8 1
Rudimentary cesspit/Ditch 96.2 3.2 0.247
Water supply
Public network 3.8 1 0.807
Well/water-hole/clay pit/water truck 96.2 1.27
Treated 46.2 1
Filtered or untreated 53.8 1.07 0.847
Total number of people in the residence
1-5 people 57.7 1
6 or more people 42.3 1.38 0.398
Maternal factors 42.3 1.38 0.398
Maternal factors
Maternal age
≤ 19 years 88.5 0.78 0.681
> 19 years 11.5 1
Maternal height (tertile)
1º (1.415 - 1.497m)
2º (1.497 - 1.533m)
53.9
26.9
1.39
0.82
0.045
0.528
2.33
0.78
0.102
0.707
3º (1.533 - 1.67m) 19.2 1 1
Maternal BMI
Underweight 18.2 2.45 0.172 1.61 0.469
Eutrophy 50 0.71 0.541 0.64 0.438
Overweight 13.6 0.44 0.273 0.39 0.195
Obesity 18.2 1 1
Healthcare and nutrition
Family Health Strategy - ESF
Yes 24 1
No 76 0.60 0.260
Community Health Worker's visit
Yes 88.4 1
No 11.6 1.14 0.821
Aleitamento materno exclusivo
Sim 66.7 1
Não 33.3 0.98 0.975
Characteristics of birth
Birth weight
< 2500 g
≥ 2500 g
15
85
1.37
1
0.599
Child's morbidity
Diarrhea in the last two weeks
Yes
No
19.2
80.8
1
1.72
Cough in the last two weeks
Yes 42.3 1
No 57.7 0.77 0.495
Fever in the last two weeks
Yes 27.3 1
No 72.7 0.75 0.672

Discussion

This study observed a high prevalence of malnutrition, considered mild severity for the H/A deficit and moderate for the W/H deficit16. The factors associated with stunting were the lower maternal height, and, initially, the child’s age and maternal height were associated with wasting.

The high prevalence of malnutrition observed here is related to the environmental factors of the families of the children evaluated, which are mostly included in lower economic classes and with lower purchasing power.

Controversially, the mean Z-score of the H/A indicator (-0.74) of the children evaluated was closer to the adequacy value (-2.0), when compared to the national average (-1.32), meanwhile the mean W/H (-0.12) was lower than the national average (0.17)17.

The height-for-age deficit is commonly associated with long-term food deprivation and frequent infections5,6,17-21. Restrictions on linear growth tend to occur before two years of age with severe effects under the child’s psychomotor development, especially in school performance22-25. However, in this study, the prevalence of height deficit was evenly distributed among all the children’s age groups.

The prevalence of height deficit found exceeded that of other studies with Brazilian children with or without black ancestry2,5,6,11,15,18,19-23,26. The highest prevalence of global stunting is in South Asia (46%) and Sub-Saharan Africa (38%)25. The value found here neared that found for Latin America and East Asia (16%)25, while it was almost half the prevalence of developing countries (32%)25, in which Brazil ranks.

The height deficit prevalence of 15.1%, observed in this study is five times that of the reference population (2-3%)27, evidencing the level of nutritional risk to which quilombola children are exposed. It is observed that residents of traditional communities such as these still live with limitations regarding improving their nutritional status, such as low income and schooling, informality in labor relationships and difficult access to goods and services, factors partially overcome by the rest of the Brazilian child population1,7.

In this study, low maternal height was the only variable associated with height deficit in children younger than 60 months. Admittedly, women with lower heights tend to generate concepts with equally low length and likely limited growth in comparison with the children of women with normal or high height15,24,27. This relationship may be associated with restricted development and growth in the maternal uterus, as well as perpetuating the cycle of chronic malnutrition due to the maintenance of low height through subsequent generations28,32.

Although maternal height is also known for its cause-effect relationship with low birth weight, this study did not evidence any association of birth weight with restrictions on children’s linear growth22,29,30.

Low weight-for-height is one of the strongest indicators of infant mortality for the under-five age group25. It is commonly associated with more acute forms of food deprivation or infectious episodes25, unlike H/A. The prevalence of deficit in this indicator was higher than the one reported in the scientific literature5,6,15,18,19,21,23,25,31,32.

A systematic review of the nutritional status of Brazilian children revealed that the wasting breadth ranged from 0-5%29, classified as a problem of mild severity16. The overall prevalence of this disease is 7.7%31, and the highest prevalence levels in the world are in South Asia (16%) and Sub-Saharan Africa (7.8%)31. The value found in this study is also close to the prevalence observed in developing countries (7.7%)31. In this study, the deficit found was also higher than expected for the reference population (2-3%)27, more than twice the upper limit.

Weight-for-height was homogeneous when distributed by children’s gender. However, when classified by age, we observed that children younger than 24 months had a higher propensity to develop low weight, corroborating data from the literature that indicate the population of under two years of age as the most affected in delayed weight gain5,32,33.

The emaciation caused by the deficit in this indicator portrays a rupture in the child’s physical harmony13,15, possibly caused by inadequate weight gain, despite normal growth or temporary weight loss due to common childhood morbidities, such as cough and diarrhea34. However, this study did not find an association of morbidity episodes with the deficit in this indicator, probably attributing to the W/H deficit the reduced weight gain, which could not be evaluated due to the cross-cutting nature of this study.

The prevalence of weight and height deficits suggests that quilombola children under 60 months of Penalva and Viana still live with inaccessibility to essential services. The prevalence levels closest to those found in this study were in poorer geographic regions, mainly on the African continent, where the ancestors of quilombo remnants originate2,5,6,11,15,18,19-23,25,26,31,32.

This work’s design was limited regarding data collection in two municipalities of the same geographic region, without taking into account the distribution of the quilombola population in other municipalities in Maranhão, which does not allow to infer these results for all quilombola communities in the state. Also, the lack of food intake assessment of this population restricted the verification of inadequacies in the children’s diet, which could explain the malnutrition found.

The survey of information in a representative sample in the quilombo remnant communities in the state of Maranhão is a pioneer initiative to analyze the nutritional situation of this population, which can improve understanding of malnutrition in specific populations in one of the poorest states of the country and, therefore, to direct increases in the public policies for this specific population group.

Conclusion

This study observed a high prevalence of height deficit and low weight-for-height in the sample of quilombola children in two municipalities in the state of Maranhão. The lower maternal height was related to infant height deficit. The results expose the situation of social inequity and invisibility to which this population is submitted and point to the need for public policies that aim to compensate for the historical neglect of the State towards this population segment.

Acknowledgments

We are grateful to the State Health Secretariat of Maranhão and the Secretariat for the Promotion of Racial Equality Policies for the logistical and financial support. We are also grateful to the Santo Antônio dos Pretos Association for their support and permission to conduct the research, as well as all who have contributed directly or indirectly to this work.

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Received: November 15, 2017; Accepted: September 25, 2018; Published: September 27, 2018

Collaborations

VNC Silveira worked on the interpretation of the data writing of the article and approval of the version to be published. MTBA Frota worked on the design, critical review of the work and approval of the version to be published. LL Padilha worked on data analysis, critical review of the work and approval of the version to be published.

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