The relationship between serum retinol concentrations and subclinical infection in rural Brazilian children

Relação entre as concentrações séricas de retinol e a infecção subclínica em crianças rurais brasileiras

ABSTRACT

Objective

To evaluate the relationship between serum retinol concentrations and subclinical infection in children from rural settlements.

Methods

A cross-sectional population-based study was carried out in nine rural settlements in the northeastern region of Brazil, involving 118 children aged 6 to 59 months. The relationship between serum retinol and C-Reactive Protein levels, an important marker of infectious and inflammatory processes, was investigated by multiple linear regression, controlling for demographic, socioeconomic and nutritional variables. Serum retinol and C-Reactive Protein were measured, respectively, by High Performance Liquid Chromatography and immunoturbidimetric assay in automated equipment.

Results

Vitamin A deficiency (retinol <0.70μmol/L) was identified in 9.3% of the children. C-Reactive Protein was the only predictor of retinol concentrations in the final regression model, causing a 0.728μmol/L reduction in retinol concentrations in the studied children (p=0.008).

Conclusion

Vitamin A deficiency is a problem of mild/moderate severity and measures to control infectious diseases in this population are fundamental to prevent and/or combat this problem.

Keywords
Child; preschool; Infant; Infection; Rural area; Vitamin A

RESUMO

Objetivo

Esta pesquisa teve por objetivo avaliar a relação entre concentrações séricas de retinol e infecção subclínica, em crianças de assentamentos rurais.

Métodos

Trata-se de estudo transversal, de base populacional, realizado em nove assentamentos rurais na região nordeste do Brasil, envolvendo 118 crianças de 6 a 59 meses de idade. A relação entre retinol sérico e níveis de proteína C-reativa, importante marcador de processos infecciosos e inflamatórios, foi investigada por análise de regressão linear múltipla, controlando-se variáveis demográficas, socioeconômicas e nutricionais. O retinol sérico e a proteína C-reativa foram medidos, respectivamente, por Cromatografia Líquida de Alta Performance e ensaio imunoturbidimétrico em equipamento automatizado.

Resultados

A deficiência de vitamina A (retinol <0,70μmll/L) foi identificada em 9,3% das crianças. A proteína C-reativa foi o único preditor de concentrações de retinol no modelo de regressão final, causando uma redução de 0,728μmol/L nas concentrações de retinol nas crianças estudadas (p=0,008).

Conclusão

A pesquisa concluiu que a deficiência de vitamina A é um problema de severidade leve/moderada, sendo fundamental a adoção de medidas para controlar doenças infecciosas nessa população, bem como para prevenir e/ou combater o problema.

Palavras-chave
Pré-escolar; Lactantes; Infecção; Zona rural; Vitamina A

INTRODUCTION

The main manifestations of Vitamin A Deficiency (VAD), an essential micronutrient related to cell growth, immunity and vision, are associated with increased rates of infant morbidity and mortality [¹]. It is estimated that 190 million children under the age of 5 years worldwide have low serum retinol concentrations (<0.70μmol/L). The prevalence of VAD in Brazil is high among children aged 6 to 59 months [²], with a predominance of the condition in the northeastern, where there have been rates around 20% [³].

Populations living in poor rural areas tend to be more vulnerable to nutritional deficiencies and infection. In Brazil, the latest form of rural organization, called “settlements”, established by government policies has grown extensively over the past few years. However, most of these settlements still do not have the necessary infrastructure, predisposing the population to infections [⁴,⁵].

Within this context, the objective of the present study was to assess the relationship between serum retinol concentrations and subclinical infection in children aged 6 to 59 months living in the settlements of the northeastern region of Brazil.

METHODS

A cross-sectional, population-based study was conducted in the settlements of the Instituto Nacional de Colonização e Reforma Agrária (INCRA, National Institute for Colonization and Agrarian Reform), Teresina, Piauí, Brazil. Teresina is the capital of the state of Piauí, one of the poorest states in the country, located in the northeastern region of Brazil. In 2010, the mean per capita income was R$757.57 (approximately US$253.00) and the Human Development Index (HDI) was 0.751 [⁶]. According to INCRA data [⁷], Teresina has nine settlements created through the Federal Agrarian Reform between 2005 and 2008, which benefit 475 families within a total area of 6,746.97 hectares.

All children within the eligible age range from the nine settlements were invited to participate in the study, for a total of 132 children. There were 14 losses, including 3 (2.27%) due to refusal of the responsible person, 6 (4.54%) due to the absence of the legal guardian of the child at the residence, and 5 (3.78%) because of insufficient blood sample for biochemical analysis. Thus, the final sample consisted of 118 children who met the following inclusion criteria: living in the settlement, age 6 to 59 months, and free and formal consent of the parents who agreed to the child’s participation by signing the free informed consent form.

Data collection

The data were collected from May to October 2013. The field team, which was trained by the supervisors of the project, consisted of nutritionists and nutrition students from the Universidade Federal do Piauí (UFPI, Federal University of Piauí).

Socioeconomic and demographic variables

Socioeconomic and demographic data of the families were collected using questionnaires during the home visits. The criteria of the Brazilian Association of Research Companies [⁸] were used for the classification of the socioeconomic status of the families. At the end of the interview, a date was scheduled for blood collection, anthropometry, and evaluation of food intake and health of the child.

Measurement of serum retinol and C-Reactive Protein (CRP)

Blood samples (3–5 mL) were collected by venipuncture into tubes without anticoagulant (Greiner Bio-One, São Paulo, Brazil) wrapped in aluminum foil for protection from light. Maintaining the cold chain, the samples were transported to the Laboratory of Experimental Nutrition, Department of Nutrition, UFPI, where they were centrifuged at 3,000rpm and divided into two serum aliquots. The two aliquots were stored in amber and transparent microtubes for the measurement of retinol and C-Reactive Protein, respectively, at 80ºC until the time of analysis.

Serum retinol was measured at the Laboratory of Micronutrients, School of Public Health, University of São Paulo, by High-Performance Liquid Chromatography (HLPC) in a Solvent Delivery Module LC-10Avp (Shimadzu^® Corporation, Analytical Instruments Division, Kyoto, Japan) as described by Arnaud et al. [⁹]. VAD was diagnosed when serum retinol concentrations were less than 0.70µmol/L. With respect to the level of epidemiological importance, the following prevalence classification was adopted: 2 to 10%, mild public health problem; 11 to 19%, moderate public health problem, or >20%, serious public health problem [¹⁰].

Measurement of CRP

C-Reactive Protein was measured in the samples at the Laboratory of Clinical Analyses, University Hospital, UFPI, by an immunoturbidimetric assay in an automated Cobas Integra Plus 400 biochemical analyzer (Roche^® Diagnostics, Mannheim, Germany) using the CRP kit (Cassete C-Reactive Protein Roche^®). A level of CRP>5mg/L was defined to indicate the presence of infection or of an inflammatory process.

Anthropometry

The weight of the children was measured with a digital scale (Plena^®, São Paulo, Brazil; capacity of 150kg) to the nearest 100g. Children younger than 2 years were weighed on the arms of the responsible person whose weight was deduced from the total weight. Height was measured with a fabricated infantometer (measuring range of 100cm and subdivisions in millimeter) in children younger than 2 years and with a stadiometer (Seca^®, Hamburg, 206, Germany) containing a 2.2 measuring tape and subdivisions in millimeter in children older than 2 years. Nutritional status was evaluated based on height/age, weight/age, weight/height, and Body Mass Index (BMI)/age indices [¹¹].

Food intake

Food intake was evaluated using a 24-hour diet recall by interview with the mother or responsible person of the child. If the children attended daycare centers or nursery schools, the employees responsible for the preparation and distribution of the child’s meal at the institutions were also interviewed. Photographic records of the utensils and portions [¹²] were used to help the interviewed subjects identify the amounts of foods ingested and conversion tables [¹³,¹⁴] were applied to transform the home measures into gram (g) or milliliter (mL).

For the estimation of intrapersonal variability, a second 24-hour recall was applied to 40% of the sample selected randomly after an interval of 2 months, repeating the same procedure as used in the first interview. Habitual nutrient intake was estimated using the Multiple Source Method (version 1.0.1) [¹⁵].

The amounts of nutrients were calculated using the Nutwin 1.5 software [¹⁶]. The foods not found in the database of the program were inserted based on chemical composition tables of the foods [¹⁷-¹⁹]. For processed foods not included in these tables, the nutritional information on the labels of the products was considered. Regional preparations were included in the program according to the ingredients and home quantities described in the form.

The intake of vitamin A (µg), proteins (g), lipids (g), iron (mg), and zinc (mg) was evaluated, the last four because they are involved in the bioavailability of vitamin A [²⁰-²²]. The reference values proposed by the Institute of Medicine were used for the evaluation of nutrient intake [²³]. The Estimated Average Requirement (EAR) was adopted as the cut-off for calculation of the prevalence of inadequacy. In the case of nutrients for which no EAR was available, the Adequate Intake (AI) was used. In these cases, it was not possible to estimate the prevalence of inadequacy. The volume of milk consumed by breast-fed children was estimated according to the Brazilian Food Guide for children under the age of 2 years [²⁴].

Data of the child

A questionnaire was applied to the person responsible for the child to obtain data regarding breast-feeding practices, presence of morbidities in the last 15 days, and use of vitamin complexes. The date of birth of the child and information about vitamin A supplementation in the last 6 months were collected from the Child’s Health Card.

Statistical analysis

The data were processed and analyzed using the Statistical Package for the Social Sciences (SPSS Inc., Chicago, Illinois, United States) 20.0. The Kolmogorov-Smirnov test was used to evaluate the normality of the dependent variable (serum retinol concentrations). Natural logarithmic transformation was necessary to obtain normality of the data. Levene’s test was used to verify the homogeneity of variances. In bivariate analysis, the Student t-test and analysis of variance were used for comparison between serum retinol concentrations and variables with two or more categories, respectively. Numerical variables were compared using Pearson’s correlation coefficient. A level of significance of 5% was adopted. The variables showing p<0.20 in bivariate analysis were included in the multiple linear regression model (backward stepwise method). In this case, significance was assumed when p<0.05.

RESULTS

Among the 118 children studied, 59.3% were girls, with a mean age of 30.37 (16.68) months (Table 1). The mean serum retinol level was 1.33 (0.57) µmol/L and the prevalence of VAD was 9.3%.

Table 1
Characteristics of the population (n=118).

Variables		n	%		Mean	SD
Child age (months)					30.37	16.68
Child’s gender
	Female	70	59.3		-
	Male	48	40.7		-
Socioeconomic class
	C and D	10	08.5		-
	E	108	91.5		-
Government assistance
	Yes	86	72.8		-
	No	32	27.2		-
Access to health services
	Local health center	3	02.5		-
	Municipal health center	98	83.1		-
	Municipal hospital	15	12.7		-
	Other	2	01.7		-
Type of dwelling
	Mud/unfinished masonry	58	49.2		-
	Finished masonry	60	50.8		-
Presence of piped water
	Yes	100	84.7		-
	No	18	15.3		-
Waste destination
	Septic tank	90	76.3		-
	Open sky	28	23.7		-
Public garbage collection
	Yes	53	44.9		-
	No	65	55.1		-
Use of vitamin complexes (last 3 months)
	Yes	18	15.3		-
	No	100	84.7		-
Vitamin A supplementation (last 6 months) *
	Yes	70	61.9		-
	No	43	38.1		-
Exclusive breast-feeing †
	<1 month or never	23	20.0		-
	1 to 5 months	38	33.0		-
	6 months	37	32.2		-
	>6 months	17	14.8		-
Health complications (in the last 15 days)
	Diarrhea	7	05.7		-
	Vomiting	5	04.1		-
	Parasitosis	5	04.1		-
	Respiratory diseases	65	52.8		-
Presence of subclinical infection ‡
	Yes	14	11.9		-
	No	104	88.1		-
Maternal age (years)		-			026.30	005.62
Maternal education level (years of schooling)		-			006.81	003.10
Paternal education level (years of schooling)		-			006.57	003.60
Number of household members		-			004.83	001.79
Household income (R$)		-			859.36	437.00
Per capita household income (R$)		-			190.95	109.66
Number of rooms		-			005.00	001.37
Number of persons per room		-			001.04	000.43
Anthropometry (Z-score)
	Weight for height	-			000.20	000.93
	Weight for age	-			00-0.10-	000.99
	Height for age	-			00-0.44-	001.15
	BMI for age	-			000.24	000.94
Nutrient intake
	Proteins (g)	-			057.10	25.2
	Lipids (g)	-			035.80	09.7
	Vitamin A (µg)	-			286.80	99.9
	Iron (mg)	-			008.00	02.5
	Zinc (mg)	-			005.50	02.2

• Note:
• ^*
  Interviewee could not answer.
• ^†
  The child had not health booklet.
• ^‡
  Assessed by C-Reactive Protein concentrations >5mg/L. BMI: Body Mass Index; SD: Standard Deviation.

As can be seen in Table 2, vitamin A intake was inadequate in almost 100.00% of children aged 48 to 59 months (99.98%). Another finding that calls attention is the high percentage of inadequate iron intake, especially among children aged 7 to 11 months (99.66%). Mean zinc intake was higher than the EAR in children older than 12 months, with low percentages of inadequacy. With respect to macronutrients, mean protein intake was above the EAR and AI for the corresponding age groups. Mean fat intake was lower than the AI in children under the age of 1 year.

Table 2
Habitual nutrient intake in the population (n=118).

Nutrients		EAR/ IA	Mean	SD	Percentiles of nutrient intake			Prevalence of inadequacy %
					25th	50th	75th
6 months
	Proteins (g)*	009.10	013.5	01.5	012.3	013.3	014.7	-
	Lipids (g)*	31	027.6	06.6	023.7	030.0	031.5	-
	Vitamin A (µg)*	400	671.9	97.9	609.7	701.9	734.1	-
	Iron (mg)*	000.27	004.4	00.8	003.9	004.1	005.0	-
	Zinc (mg)*	2	001.6	00.1	001.5	001.5	001.7	-
7-11 months
	Proteins (g)	9	025.9	07.4	019.8	023.7	029.4	01.13
	Lipids (g)*	30.0	026.2	08.8	022.0	026.3	032.8	-
	Vitamin A (µg)*	500	381.5	56.7	322.2	404.8	430.4	-
	Iron (mg)	06.9	003.1	01.4	001.9	002.6	004.3	99.66
	Zinc (mg)	02.5	002.5	00.8	002.1	002.3	003.0	0
12-47 months
	Proteins (g)	11	058.9	19.9	042.9	056.4	069.6	00.80
	Lipids (g)†	-	036.0	05.0	032.6	036.2	038.6	-
	Vitamin A (µg)	210	280.4	75.7	218.2	274.9	330.4	17.62
	Iron (mg)	03.0	008.1	02.0	006.6	007.9	0v9.3	00.54
	Zinc (mg)	02.5	005.7	01.2	004.9	005.5	006.4	00.40
48-59 months
	Proteins (g)	13	071.0	27.8	055.9	071.0	084.8	01.88
	Lipids (g)†	-	042.3	14.5	031.7	041.2	049.7	-
	Vitamin A (µg)	275	213.3	16.2	201.3	211.6	224.3	99.98
	Iron (mg)	04.1	009.8	02.5	008.1	009.6	010.9	01.13
	Zinc (mg)	4	007.0	02.7	005.4	006.5	008.4	13.35

• Note:
• ^*
  IA: Inadequate intake as reference value.
• ^†
  Dietary reference intake not determined. Other nutrients = EAR: Estimated Average Requirement. BMI: Body Mass Index; SD: Standard Deviation.

Analysis of the categorical variables showed that serum retinol concentrations were significantly lower in children living in dwellings made of mud and unfinished masonry (p=0.025) and in those diagnosed with subclinical infection (p=0.008). With respect to the numerical variables studied, vitamin A intake and retinol concentrations showed a weak and positive, but significant association (r=0.118; p=0.049) (Table 3).

Table 3
Characteristics of the population according to serum retinol concentrations (µmol/L) (n=118).

Variables		Mean*	SD	r†	p
Child age (months)		-		-0.125	0.178
	Child’s gender
	Female	1.31	0.61	-	0.511
	Male	1.35	0.52
Socioeconomic class
	C and D	1.47	0.71	-	0.622
	E	1.32	0.56
Government assistance
	Yes	1.32	0.57	-	0.778
	No	1.36	0.57
Access to health services
	Local health center	2.09	0.53	-	0.140
	Municipal health center	1.32	0.54
	Municipal hospital	1.32	0.68
	Other	1.08	0.75
Type of dwelling
	Mud/unfinished masonry	1.21	0.52	-	0.025
	Finished masonry	1.44	0.60
Presence of piped water
	Yes	1.34	0.56	-	0.614
	No	1.29	0.61
Waste destination
	Septic tank	1.39	0.59	-	0.063
	Open sky	1.16	0.48
Public garbage collection
	Yes	1.33	0.58	-	0.794
	No	1.34	0.56
Use of vitamin complexes (last 3 months)
	Yes	1.27	0.35	-	0.955
	No	1.34	0.60
Vitamin A supplementation (last 6 months)
	Yes	1.02	0.55	-	0.189
	No	1.38	0.56
Exclusive breast-feeing
	< 1 month or never	1.30	0.46	-	0.170
	1 to 5 months	1.40	0.60
	6 months	1.37	0.62
	> 6 months	1.06	0.45
Health complications
	Diarrhea	1.50	0.81	-	0.503
	Vomiting	1.52	0.77
	Parasitosis	1.52	0.50
	Respiratory diseases	1.29	0.54
Presence of subclinical infection
	Yes	1.02	0.55	-	0.008
	No	1.38	0.56
Maternal age (years)		-		0.009	0.921
Maternal education level (years of schooling)		-		0.053	0.574
Paternal education level (years of schooling)		-		-0.002	0.987
Number of household members		-		-0.062	0.508
Household income (R$)		-		0.070	0.450
Per capita household income (R$)		-		0.098	0.290
Number of rooms		-		0.088	0.345
Number of persons per room		-		-0.111	0.232
Anthropometry (Z-score)		-
	Weight for height	-		0.117	0.206
	Weight for age	-		0.064	0.490
	Height for age	-		-0.018	0.851
	BMI for age	-		0.116	0.211
Nutrients
	Proteins (g)	-		0.044	0.667
	Lipids (g)	-		0.005	0.960
	Vitamin A (µg)	-		0.118	0.049
	Iron (mg)	-		-0.064	0.488
	Zinc (mg)	-		-0.008	0.934

• Note:
• ^*
  Student t-test and analysis of variance for comparison between serum retinol concentrations and variables with two or more categories, respectively.
• ^†
  Pearson’s correlation coefficient.
• ^‡Assessed by C-Reactive Protein concentrations >5mg/L. BMI: Body Mass Index; SD: Standard Deviation.

The final multiple linear regression model (Table 4) showed that the presence of subclinical infection caused a reduction of 0.728µmol/L in retinol concentrations (p=0.008), explaining 51.1% of the variability in serum retinol in the population studied.

Table 4
Final multiple linear regression model considering serum retinol concentration as the dependent variable (outcome).

Variables	Coefficients		T	p	Exp(B)*	95%CI for Exp(B)
	B	Standard error				Lower limit	Upper limit
(Constant)	0.238	0.040	5.906	0.000	1.269	1.171	1.374
Presence of subclinical infection†	-0.317	0.117	-2.708	0.008	0.728	0.578	0.919

• Note:
• ^*
  Data converted to their original values by exponential transformation.
• ^†
  Assessed by C-Reactive Protein concentrations >5mg/L. ANOVA (p=0.008), normality (p=0.946), homogeneity (p=0.723), R²=51.1%.

DISCUSSION

The mean serum retinol concentrations of the children studied were within the normal range; however, regarding the concentrations identified as low, the percentage found (9.3%) classifies VAD as a mild public health problem.

Low vitamin A intake, as well as infectious processes, can cause a reduction in blood retinol concentrations. In the first case, there is a decrease in liver stores. In the second case, vitamin A concentrations stored in the liver may be normal, but mobilization of the vitamin is suppressed as a result of the low synthesis of the retinol transport protein, also as a consequence of infectious processes [²⁵].

In this study, the presence of subclinical infection was inversely associated with serum retinol concentrations. Similar results have been reported in other studies. Rohner et al. [²⁶] showed a significant increase in the risk of VAD in children diagnosed with inflammation, demonstrated by elevated concentrations of CRP and alpha-1-acid glycoprotein.

The prevalence of VAD was 9.3%, but the prevalence of subclinical infection, assessed by CRP concentrations, was 11.9%. It is important to emphasize that retinol-binding protein is a negative acute phase protein, and that the occurrence of a subclinical infection can interfere with its serum concentrations [²⁷]. Excluding from the final sample (n=118) the children with subclinical infection (n=14), the prevalence of VAD is reduced to 7.7%. This reduction may reflect an overestimation of 1.6% of the overall prevalence of low serum retinol concentrations, in agreement with the study of Silva et al. [²⁸] who reported an overestimation of 4.1%.

With respect to the variables related to food intake, vitamin A intake was significantly associated with serum retinol concentrations, although this association was no longer observed in the final Multiple Linear Regression (MLR) model. The perception of the influence of vitamin A intake on serum retinol concentrations has been shared by some authors [²⁹-³¹].

One of the limitations of the present study, in addition to those inherent to dietary surveys, was the fact that two persons were interviewed (the mother or responsible person of the child and employees of daycare centers or nursery schools). Additional limitations include the lack of control of seasonality, since some foods such as fruits are generally influenced by this factor [³²], and the existence of different food composition tables, which often do not contain adequate information about the content of regional foods. Despite these limitations, care was taken in this study to minimize potential measurement errors resulting from the use of the data collection instrument.

CONCLUSION

The variables associated with serum retinol concentrations in this population were the presence of subclinical infection. Vitamin A deficiency is a mild public health problem in the children studied. These results indicate the need to implement public policies designed to control infectious diseases and nutritional interventions that stimulate the consumption of foods containing vitamin A in order to prevent and/or combat not only VAD, but also other nutritional deficiencies that are common in this age group.

CONTRIBUTORS

LFS TELES participated in the development of the study protocol, data collection and analysis,interpretation of the results, and writing of the manuscript. AA PAIVA was responsible for the designof the study and coordination of the research, and participated in the interpretation of the results andwriting and revision of the manuscript. LA LUZIA performed the retinol analysis and participated inthe revision of the manuscript. FEL LIMA-FERREIRA participated in the analysis of food intake and revisionof the manuscript. CMRG CARVALHO participated in the data analysis and the revision of the manuscript.PHC RONDÓ participated in the revision of the manuscript and retinol analysis.

• Support: Conselho Nacional de Desenvolvimento Científi co e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (Edital CASADINHOPROCAD, grant 552239/2011-9) for fi nancial support. L.F.S.
• Article based on the master thesis of LFS TELES, entitled “Deficiência de vitamina A e fatores relacionados à retinolemia em crianças de seis a cinquenta e nove meses de idade em assentamentos rurais de Teresina”. Universidade Federal do Piauí, 2015.

Como citar este artigo/How to cite this article

• Teles LFS, Paiva AA, Luzia LA, Lima-Ferreira FEL, Carvalho CMRG, Rondó PHC. The relationship between serum retinol concentrations and subclinical infection in rural Brazilian children. Rev Nutr. 2018;31(3):299-310. http://dx.doi.org/10.1590/1678-98652018000300004

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Publication Dates

• Publication in this collection
  May-Jun 2018

History

• Received
  04 Apr 2018
• Reviewed
  12 July 2018
• Accepted
  02 Aug 2018