Skip to main content
Download PDF
Download ePub

Association between vitamin A status, inflammations, and infections in children 36–59 months of age in rural Burkina Faso: A cross - sectional study

Journal of Health, Population and Nutrition volume 44, Article number: 107 (2025) Cite this article

Abstract

Background

Assessing vitamin A (VA) status using retinol and retinol-binding protein (RBP) in the presence of infection and inflammation remains challenging, as both markers prove to be unreliable during such physiological disturbances.

Objective

This study aimed to assess the association between common infections and inflammation and VA status of children in rural Burkina Faso.

Methods

Two community-based cross-sectional studies were conducted in the villages of Sourkoudougou and Banakeledaga, in Southwestern Burkina Faso, one during the dry season (November 2016– January 2017) and the second during the rainy season (August– September 2017). In total, 115 children, 36–59 months of age, were included. The 13C-retinol isotope dilution test (RID) was used to assess total body VA stores (TBS) and VA total liver reserves (TLR). Malaria infection and intestinal parasites were evaluated at enrollment. Serum C-reactive protein (CRP) and alpha-1-acid glycoprotein (AGP) were measured. Univariable and multivariable linear regressions were used to test the associations between VA status and infection and inflammation status.

Results

No VA deficiency (TLR ≤ 0.1 µmol/g liver) was detected using RID method. Geometric means (95% confidence interval) of TBS and TLR were respectively 473 (412; 543) µmol and 0.86 (0.75; 0.99) µmol/g liver. One-third of study participants were found to have hypervitaminosis A (TLR > 1.0 µmol/g liver). Elevated CRP (> 5.0 mg/L) and AGP (> 1.0 g/L) were respectively detected in 1.9% and 28.6% of children. Positive malaria was diagnosed in 5 children. Intestinal parasites were found in one out of two (47.6%) participants, and other morbidities were detected in 2 participants. In a multivariable adjusted regression, significant positive weak associations were found between Log TLR and CRP concentrations (N = 79, β = 0.058, p = 0.004) and between Log TBS and CRP concentrations (N = 79, β = 0.054, p = 0.005).

Conclusion

Study children were apparently healthy with high prevalence of asymptomatic intestinal parasites and chronic inflammation. TLR and TBS were positively associated with the acute phase protein CRP warranting further investigation.

Trial registration

The study was registered retrospectively (22 March 2018) as a clinical trial with the Pan African Clinical Trials Registry (Cochrane South Africa; PACTR201803002999356).

Introduction

Vitamin A (VA) plays an important role in supporting sight, maintaining the functioning of the immune system of individuals, and in children’s growth and development [1]. Vitamin A deficiency (VAD) can lead to anemia, weakened resistance to infections, blindness, and death [2, 3]. Severe VAD remains a serious public health problem particularly in vulnerable populations of children and pregnant women in low- and middle-income countries (LMICs) [4].

Dietary VA in the form of retinol and provitamin A carotenoids is first metabolized in the intestine, absorbed in the form of retinyl esters, transported in the lipid core of chylomicron, and stored, in its majority (90%), in the liver during adequate VA status [5]. Vitamin A (95% all-trans-retinol) is transported principally by plasma retinol-binding protein (RBP) to the tissues. Plasma RBP exists in a ratio of 1:1 with plasma retinol [6]. Plasma (or serum) RBP concentration is a preferred biomarker of VA status in field surveys where storage and laboratory capacities are limited. During an inflammatory process, acute phase proteins (APPs) are induced and regulated by cytokines. C-reactive protein (CRP) and α-1-acid glycoprotein (AGP), two biomarkers of inflammation commonly measured, are enhanced by the cytokine’s Interleukin-6, Interleukin-1, and Tumor Necrosis Factor [7]. The rise in CRP concentrations occurs 4–6 h post-infection and corresponds to an acute response to the inflammatory stimulus with a much slower and longer response by AGP [8,9,10]. The acute phase response has a transient negative influence on retinol and RBP mainly because RBP is a negative APP [4, 9,10,11]. Evidence is strong that both retinol and RBP are poor indicators of VA status during inflammation. Additionally, the ratio retinol: RBP of 1:1 may be affected by VA status, inflammation, and nutritional status [11,12,13]. Previous studies found that RBP and retinol concentrations potentially overestimated the prevalence of VAD in populations with high levels of inflammation, making the assessment of VAD difficult when infections are common [11, 12, 14,15,16]. Adjusting for inflammation indicators improves the accuracy of VAD prevalence estimates based on plasma or serum retinol or RBP concentrations [17]. Wessells and coauthors suggested that asymptomatic malaria affects VA indicators, hence the importance of adjusting for it [18].

It is evident that severe or recurrent infections can lead to the development of VAD, at least in subjects who have low-to-marginal intakes of VA [11]. Furthermore, infections and high concentrations of APP are highly associated during VAD [19, 20]. VAD results in increased macrophage-mediated inflammation through the enhanced production of Interleukin 12 (IL-12) and Interferon gamma (IFN-γ) cytokines and the reduced phagocytic capacity of macrophages resulting in exacerbated inflammation [21,22,23].

Infections, inflammation, and VAD are prevalent in low income settings including Africa [24]. In Burkina Faso, VAD is still a major nutritional concern with varying prevalence from rural to urban settings [25]. In the presence of common infections and the high prevalence of VAD and inflammation, and the bidirectional relationship between VAD and inflammation or the immune response, it becomes difficult to assess VA status using serum concentrations of retinol and RBP. Liver biopsy and autopsy samples are considered to be the reference methods to assess VA status. Retinol isotope dilution (RID) has been promoted as a sensitive method in assessing VA status throughout a large spectrum from depletion to toxicity [26]. This study aims at assessing the association between inflammation and infections and VA status using the 13C-RID test in Burkinabe children 36–59 months of age.

Materials and methods

Study area

The study was conducted in the villages of Sourkoudougou and Banakeledaga. Both villages are located in the health district of Dandé, which is located in the “Hauts-Bassins region” at 30 km from the main city of Bobo-Dioulasso. The climate is Soudano-Sahelian and characterized by two seasons, a dry season lasting between October– May and a rainy season between June and September. The region receives 800 to 1200 mm of irregular rainfall. The rainy season is characterized by a high prevalence of common infections including malaria and diarrhea. Agriculture remains the dominant economic activity throughout the health district of Dandé. Staple crops, including maize, rice and sweet potatoes, are grown during the rainy season. A variety of irrigation-based garden vegetables and fruits are cultivated using water from a river that crosses the two villages. The district has poor sanitation facilities. The situation is exacerbated during the rainy season, which makes the river and many small swamps a breeding ground for mosquitoes, the vector of malaria and other infectious diseases. As a result, malaria and diarrhea are the main causes for medical consultation and hospitalization among children under five years of age [27]. Furthermore, malnutrition is a significant public health concern, primarily affecting children under the age of five in this setting [27].

Study population

The study population consisted of 115 preschool children, 36–59 months of age from both sexes, with an ascertained birthdate, living in the two villages and not suffering from a severe or chronic illness. Children were not included if they were severely malnourished (weight-for-height z-score [WHZ] below − 3 standard deviations [SD], according to the 2006 World Health Organization (WHO) Child Growth Standards) [28]; had fever (fever was defined as an uncorrected axillary temperature above 37.5 °C) or reportedly had fever in the previous 24 h; or were suffering from serious illnesses requiring hospitalization such as severe anemia (hemoglobin concentrations < 7.0 g/dL), convulsion, coma, incoercible vomiting, severe dehydration, or severe respiratory illness.

Sample size

This study is a secondary analysis of country-specific data from Burkina Faso, derived from a larger regional African study that recruited a minimum of 50 children per site [29, 30]. The sample size estimation was based on literature recommending a sample size of 30 subjects per treatment group for isotope studies on supplementation [26, 31]. For the current study, we enrolled 55 children during the rainy season and 60 during the dry season to account for a 10% dropout rate over the 15-day protocol period and an additional 10% dropout rate over the one-month period following high-dose VA supplementation (part of a separate sub-study not within the scope of this study).

Study design and duration

Eligible children were enrolled in two community-based cross-sectional surveys during the dry season (N = 60, November 2016 to January 2017) and the rainy season (N = 55, August to September 2017) (Fig. 1).

Fig. 1
figure 1

Schematic diagram of the study design, the 13 C-retinol isotope dilution test protocol and the data collection timeline

Full size image

Socioeconomic, dietary and anthropometric data collection

Demographic and socio-economic data were collected using a semi-structured questionnaire. The birth date of the child was extracted directly from the birth certificate that the parents were asked to bring along during enrollment. Additional data included maternal age and education, parental occupation, and number of members in the household including children under 5 years old. Socioeconomic status was assessed by household characteristics and possession of a set of assets including building materials, radio, television, telephone, refrigerator, bicycle, and motorcycle. Dietary intake and information on breastmilk intake were collected using an adapted 24-h recall questionnaire, on two days within the two weeks of enrollment, one on weekday and the second on a weekend. Briefly, the mother or the caregiver who accompanied the child was asked to list all the foods and drinks that the child consumed the day before the interview, from the time they got up until the next day [32, 33]. After obtaining the list of the foods during the first step, the mother or caregiver was probed for detailed description of each food, then the quantity consumed and the detailed description of the recipe including the ingredients if the food was a mixed dish.

Height was measured to the nearest 0.1 cm with a portable length board (Seca 213, Hamburg, Germany). Weight was measured to the nearest 0.1 kg using an electronic balance (Seca 899, Hamburg, Germany). Weight and height were measured in duplicate according to standard procedures. A third measurement was done if the difference in measurements of weight was greater than 0.1 kg and of height of more than 0.5 cm. The mean value of the two closest values was used in the analysis.

Blood sample collection, stable isotope administration and procedure

To estimate total body VA stores (TBS) and VA total liver reserves (TLR), the 13C-RID test was used. For that, on day 0 (baseline), 6 mL venous blood were drawn in plain tubes from included participants by trained nurses. Afterwards, a prepared dose of 1.0 µmol 13C2-retinyl acetate was administered orally to the child, followed immediately by the oral administration of 1 ml of non-VA fortified vegetable oil to improve the absorption of the stable isotope. Collected blood samples were stored in a cool box (+ 4˚C) and transported the same day to the laboratories of the Institut de Recherche en Sciences de la Santé (IRSS, Bobo-Dioulasso). On day 14, children who completed the protocol on day 0 provided another sample of 6 mL venous blood in plain tubes. Collected blood samples were stored and transported as above.

Blood samples were centrifuged at 3000 rpm for 10 min with a Universal 320R centrifuge (Hettich Zentrifugen, D-78532 Tuttlingen) on the same day of their reception. Volumes of 1.0 to 1.5 mL of serum were transferred to brown 2 mL cryotubes (Eppendorf, Hamburg, Germany) under yellow light to protect VA indicators against photodegradation. Samples were stored at − 80 °C until shipped on dry ice to the laboratories of UW-Madison, for 13C analysis and to the VitMin Lab, Willstaett, Germany for analysis of inflammatory biomarkers.

Hemoglobin concentration, malaria, intestinal parasites and inflammation indicators

On day 0, the remaining blood drops from the venous blood draw were used to measure hemoglobin (Hb) concentration with a point-of-care HemoCue (Hb-301, Ängelholm, Sweden). Rapid diagnosis test (Malaria-Ag-Pf/Pan™) and blood smear microscopy were used to assess malaria status [34]. On a sample of 30 gram collected stool, a direct examination on a slide after preparation was performed by qualified field workers to search for the presence of intestinal parasites on site. The test was positive if at least one parasite was identified. Serum concentrations of CRP and AGP were simultaneously measured in VitMin Lab using a sandwich ELISA technique [35]. The coefficients of variation (CVs) for CRP and AGP were, respectively, 3.61% and 5.84%.

Analysis of 13C

Method of extraction, purification and analysis of 13C using gas chromatography combustion isotope ratio mass spectrometry (GC/C/IRMS) was previously described [36, 37]. Briefly to 0.3 to 1.0 mL serum, 1 ml ethanol was added to precipitate proteins. C23 β-apo-carotenol was used as an internal standard. Retinol was extracted 3 times with hexanes. Hexane layers were pooled, dried under nitrogen, resuspended in methanol (100 mL), frozen at -80˚C for 5 min, centrifuged at 1380 x g briefly, and injected into HPLC system 1 for quantification and purification. The retinol fraction was collected, dried under nitrogen, and resuspended in 100 µL methanol for injection into system 2, dried in a Thermo Savant Speed-Vacuum centrifuge (Thermo Scientific, Waltham, MA), reconstituted in 10 µl hexanes, and 1.5 µl was injected into a GC/C/IRMS. The determination of TBS of VA was detailed previously [36, 37]. After sample’s injection simulating on-column injection with the PTV injector, the δ 13C-retinol values were determined from serum samples by GC/C/IRMS in duplicate. Synthetic retinol, prepared by quick retinyl acetate saponification (Sigma-Aldrich, St. Louis, MO), was purified twice similarly to serum retinol and used as an external standard. Atom percentage (At %) was directly calculated (Isodat version 2.0; Thermo Scientific) in reference to carbon dioxide, which was calibrated against a sucrose standard (National Institute of Standards and Technology, 8542).

Assessment of VA total body store (TBS) and total liver reserve (TLR)

TBS (µmol) were calculated as previously described [37, 38] using the following equation:

TBS = a × \(\:\frac{1}{TTR}\) × (factors for absorption and storage)

Where a is the amount of 13C retinyl acetate in the dose administered (1.0 µmol); TTR is the tracer-to-tracee ratio or the fraction of 13C to 12C in the dose which was 0.11, that accounts for natural abundance. The following assumptions were used [38] in calculating TBS of VA: a 90% absorption rate of the dose, a specific activity of 0.8 because dietary access to vitamin A was not restricted in the 14 days between the two blood samples, and a half-life of 136 days.

TLRs (µmol/g) were calculated using the formula:

TLR = (\(\:\frac{\text{T}\text{B}\text{S}}{BW\left(kg\right)\times\:liver\:fraction\:of\:BW}\)) x 1000 x fraction of TBS in liver

Where BW is body weight (kg), liver fraction of BW was estimated as 3% in preschool children, and 80% of TBS were assumed to be in the liver storage pool of children with adequate to hypervitaminotic VA status [37, 38]. Hypervitaminosis A was defined as an elevated concentration of VA (> 1.0 µmol/g liver) and VA deficiency as TLR < 0.1 µmol/g liver [39].

Data processing and statistical analysis

Z-scores of height-for-age (HAZ), weight-for- height (WHZ) and weight-for-age (WAZ) were calculated using the STATA macros of the WHO Child Growth Standards [28]. Stunting, wasting, and underweight were defined as HAZ, WHZ, and WAZ < -2 SDs, respectively.

From the 24-h dietary recall data, dietary diversity score (DDS) and VA-rich food intake were constructed using the Food and Agriculture Organization (FAO) DDS with nine foods groups [40] and calculated using the consumption or not of these food groups ranging between 0 and 9. The nine food groups included: (1) Starchy foods (cereals, roots and tubers), (2) Dark green leafy vegetables, (3) VA rich fruits and vegetables, (4) Other fruits and vegetables, (5) Organ meat, (6) Meat and fish, (7) Eggs, (8) Legumes, nuts and seeds, and (9) Dairy products (milk, yogurt and cheese). Additionally, VA-rich foods were summarized as VA animal source food (preformed VA) and VA-rich plant source food (pro–VA carotenoids). The scores of VA animal source food and VA-rich plant source food ranged from 0 to 3 both [40].

Inflammation status was defined as elevated concentration of CRP (> 5.0 mg/L) and AGP (> 1.0 g/L) [17]. Anemia was defined in children with Hb concentrations < 11.0 g/dL [41].

Household asset index was constructed based on ownership of a set of assets (radio, television, telephone, refrigerator, bicycle, or motorcycle) and building materials using multiple correspondence analysis [42].

Statistical analyses were carried out using Stata software, version 15.1 (Stata Corp, TX, USA). The baseline assessments were performed by descriptive statistics [means (± standard deviation), geometric mean (90% confident interval), median (interquartile range) and proportions]. Variables that were not normally distributed (CRP, AGP, TBS and TLR) were logarithm-transformed, which were back transformed for reporting of descriptive results. As part of a quality control check, TLR values exceeding 15.0 µmol/g liver were excluded due to their implausibility. In our dataset, one data point (TLR = 27.289 µmol/g liver) was dropped.

The associations between VA status of the child and their infection status and inflammation indicators were tested using the univariate linear model, including only the dependent variables (TBS and TLR) and the independent variables (CRP and AGP concentrations, malaria status and intestinal parasite test). Another model was built including the four indicators of infection and inflammation. In a multivariate linear regression, preselected variables (covariates) were included in the model that could explain the changes in the dependent variables. They were selected based on literature and included child’s sex, age, Hb concentration, nutritional status (WHZ), DDS, and the scores of VA-rich plant source food and VA animal source food, season, family size, mother’s educational status, the occupation of household head, and household wealth index. Included co-variables were tested for collinearity and those causing the variance inflation factor (VIF) > 10 were dropped. For each model, the residue normality was tested by visual inspection of qnorm, and the equality of variances was assessed by estat hottest. P < 0.05 was considered significant. TLR and TBS were log transformed to achieve a normal distribution for these variables, ensuring the best-fitted statistical model.

In a secondary analysis, we tested how well VA status (TBS and TLR) can categorize the children based on their infection and inflammation statuses. Differences between TBS and TLR were assessed according to infection and inflammation statuses using Student t-test. Additionally, categories of infection and inflammation statuses were tested against TLR categories (high and normal) using Chi-Square test.

Results

Socio demographic characteristics of the study children, their parents and households

The study enrolled 115 children in the two cross-sectional surveys, 53 (46.1%) were female, and were aged (mean ± SD) 48.2 (± 6.8) months. The majority of children (85.1%) had normal Hb concentrations (Hb > 11.0 g/dL), 17.4% were suffering from moderate stunting (-3 SD < HAZ< -2 SD), and 7.8% were moderately wasted (-3 SD < WAZ< -2 SD). Infections were common in this study population mainly because of intestinal parasites which affected 47.6% of the children. While 5% of children tested positive for malaria. Amoeba in several forms were the most prevalent parasites and found (cyst and parasite) in 43 participants (53.1%), Giardia intestinalis in 14 participants (17.3%), and Trichomonas intestinalis in 5 participants (6.2%). Almost one-third of children had elevated AGP (28.6%) and only 2 children (1.9%) had high CRP. Most of children’s fathers (94.8%) were farmers and their mothers (79.1%) did not have any formal school education. The mean size of the family was 6.4 persons. Table 1 summarizes the main characteristics of study participants, their parents and their households.

Table 1 Baseline characteristics of participating children 36–59 months of age (N = 115) in rural Burkina Faso
Full size table

Vitamin A total body store (TBS) and total liver store (TLR)

Children in this study sample had a geometric mean (95% Confidence Interval, 95% CI) TBS of 473 (412; 543) µmol and TLR of 0.86 (0.75; 0.99) µmol/g liver. TBS and TLR were significantly higher during the rainy season (p < 0.01). During the rainy season, the geometric mean (95% CI) of TBS and TLR were 586 (475; 724) µmol and 1.10 (0.89; 1.36) µmol/g liver, respectively. During the dry season, geometric mean (95% CI) TBS and TLR concentrations were respectively, 388 (328; 460) µmol and 0.69 (0.59; 0.81) µmol/g liver for TLR. One-third (29 children, 32%) of study participants were found to have hypervitaminosis A (TLR > 1.0 µmol/g liver). None of the children were VA deficient (TLR < 0.1µmol/g liver).

Univariate linear regression analysis of the association between VA biomarkers and infection statuses and inflammation indicators

Univariate linear regressions assessing the associations between VA biomarkers (TLR and TBS) and inflammation indicators, as well as infection markers, have found no significant associations, except for associations of TLR (N = 90, β = 0.032, p = 0.041) and TBS (N = 90, β = 0.033, p = 0.036) with CRP concentration.

Assessing the differences in Log TLR and Log TBS based on the presence of acute and chronic inflammations, positive blood smear test for malaria, and the presence of intestinal parasites showed no significant differences in either indicator (Fig. 2). Similarly, when testing categories of infection and inflammation statuses against TLR categories (high vs. normal) using a Chi-Square test (Fig. 3), no significant differences were observed. In other words, the high TLR values did not show a distinct pattern concerning infection and inflammation statuses.

Fig. 2
figure 2

Distribution of total body vitamin A stores (TBS) and vitamin A total liver reserves (TLR) by season, inflammation status and infections

Full size image
Fig. 3
figure 3

Distribution of inflammation and infections categories by vitamin A total liver reserves (TLR)

Full size image

Multivariate linear regression analysis of the association between VA status biomarkers and infection status and inflammation indicators

In a multivariable model that included the four indicators of infection and inflammation, adjusted for season, child’s age and sex, mother education, family size, wealth index, DDS, VA rich food (preformed VA and pro VA) consumption score, no significant associations were found, except for a weak but significant association between log-transformed TLR and CRP concentrations (N = 79, β = 0.058, p = 0.004), and between log-transformed TBS and CRP concentrations (N = 79, β = 0.054, p = 0.005) (Table 2). The association was stronger with season, as log-transformed TLR and TBS were significantly higher during the rainy season. In contrast, the associations with wealth index showed no clear pattern, although a significantly association was observed in participants from the third quartile.

Table 2 Associations between vitamin A total liver reserves (TLR) and total body vitamin A stores (TBS) and inflammation and infections in children 36–59 months of age in rural Burkina Faso
Full size table

Discussion

The study sample had an overall high prevalence of hypervitaminosis A and none of the pre-school children was VA deficient as assessed by the 13C-RID test. Malaria was uncommon but the prevalence of intestinal parasites was high in this study sample. In this context, biomarkers of VA status including TLR and TBS were found to be significantly associated with acute inflammation indicator (CRP).

The lack of VAD is in contrast with the situation in 2008 [43] and 2014 [44], where similar research was conducted in school children in the same area and reported high prevalence (46.1% and 46.0% of children respectively) of VAD using serum retinol (< 0.7 µmol/L). Additionally, our study sample showed high prevalence of VAD, with 30.9% assessed by serum retinol (< 0.7 µmol/L) and 33.3% by RBP (< 0.7 µmol/L) [45]. Firstly, VAD is more common in pre-school children [46], yet national surveys rely on serum retinol and RBP as biomarkers for VA assessment. Secondly, previous studies used serum retinol to assess VA status, which is considered a poor indicator, particularly in the presence of infections and inflammations [47], despite adjusting for inflammation [45]. Finally, this difference could be the results of national interventions to prevent VAD. Concomitantly, national campaigns of VA supplementation and seasonal malaria prevention took place, respectively, 5 and 3 months before the present study implementation. Other countries are also reporting higher prevalence of hypervitaminosis based on TLR. In Zambia, half of the VA supplemented children (5–7 years old) have been diagnosed hypervitaminotic A (> 1.0 µmol/g liver) [37]. Around 71.6% of South African children (aged 36–60 months ) exposed to VA supplementation and fortification had elevated TLR one month after VA supplementation with 1 dose of 200,000 IU VA [48]. The current study was conducted among a relatively healthy population. Additionally, Burkina Faso has engaged in several national programs for the prevention of VAD including fortification of vegetable oil with VA, promotion of VA-rich food consumption and bi-annual supplementation with high-dose VA [49]. Our results suggest that the current multiple VA interventions should be monitored using reliable methods such as the RID to prevent the risk of VA toxicity.

The present study was conducted in an endemic malaria area where infections and inflammation are prevalent. Unexpectedly, the majority of the children tested negative for malaria parasites, were non-anemic, and had marginal levels of acute inflammation (CRP), regardless of the season. Previously, it has been reported that infections such as malaria and diarrhea were prevalent during the rainy season [50].

Indicators of VA status, TLR and TBS were found to be positively and significantly associated with serum CRP concentrations. RID parameters potentially affected by inflammation include the absorption level of the tracer [51]. In contrast to our findings, Rubin et al. detailed in their review how methods used to assess VA status, including the RID, may be affected by inflammation. Their analysis, based on a study including Zambian children, showed that the distribution curve of calculated VA reserves (micromoles per gram of liver) differed between children with and without elevated CRP levels (> 5 mg/L). Children with elevated CRP had a slightly lower distribution curve of calculated VA reserves [52], which could be attributed to reduced food intake, including vitamin A-rich foods, decreased vitamin A absorption, or increased vitamin A losses [53]. However, these results should be interpreted with cautions for several reasons. First, the observed associations were weak. Additionally, the sample size for children with high CRP values was limited, with only four participants in this category, only two of whom were included in the analysis. This constraint also limited our ability to examine interaction effects between inflammation and infections on vitamin A status. Second, the study used a cross-sectional design, which limits any interpretation regarding causality. Finally, subsequent analyses revealed no significant differences between TLR and TBS across CRP categories.

Our results showed no relationship between TLR and TBS statues and intestinal parasites. In contrast, a previous study found an association between VA status, assessed by the modified relative dose response test, and Ascaris lumbricoides in Indonesian children aged 0.6 to 6 years [54]. This association could be explained by two mechanisms. First, enteric infections can decrease the absorption of nutrients including preformed VA and pro-VA carotenoids [52]. In addition, enteric infections damage the intestinal epithelium and decrease the expression of brush-border enzymes such as lactase, as shown in a piglet model of neonatal diarrhea [52, 55]. Even if the mechanisms of this absorptive defect are unclear, previous studies documented that the impaired absorption contributed to an increased risk of VAD in children with low dietary intakes [11]. Secondly, the presence of intestinal parasites can negatively affect the absorption of 13C2-retinyl acetate, which was used in the estimation of TBS and TLR. If dose absorption is negatively impacted that would lead to a false higher dilution of tracer-to-tracee ratio (equation of TBS calculation), and consequently to an overestimation of TBS in children who are infected [38].

A key limitation of this study is the potential lack of statistical power to detect associations between inflammation, infections, and VA status, given that the sample size was primarily designed for seasonal difference rather than secondary analyses. Additionally, the low number of children with asymptomatic malaria or acute inflammation (as indicated by CRP levels) may further limit the findings. Nevertheless, an important strength of this study is the use of the RID test to determine VA status. Unfortunately, none of the children in the study had VAD, and a third of them had hypervitaminosis. To address the research question effectively, it appears essential to include children with VAD in the study for the results to be valid. Future research should consider this inclusion to provide a more comprehensive understanding of VA status in the context of prevalent inflammation and infections.

Conclusion

In a VA sufficient study sample where common infections were prevalent, TLR and TBS were positively associated with the acute phase protein CRP. Further research should be conducted to answer the primary question of this study with oversampling of participants with asymptomatic malaria infection and with VAD. Our study revealed high prevalence of hypervitaminosis in this study sample. This finding highlights the necessity for increased caution in monitoring interventions aimed at addressing VAD. Moving forward, it is important to focus on implementing sustainable and cost-effective interventions targeted at preventing VAD while minimizing the risk of adverse effects associated with excess VA intake.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

AGP:

Alpha-1-acid glycoprotein

APPs:

Acute phase proteins

At %:

Atom percentage

CRP:

C-reactive protein

CVs:

Coefficients of variation

DDS:

Dietary diversity score

FAO:

Food and Agriculture Organization

GC/C/IRMS:

Gas chromatography combustion isotope ratio mass spectrometry

HAZ:

Height-for-age z-score

Hb:

Hemoglobin

IAEA:

International Atomic Energy Agency

IFN-γ:

Interferon gamma

IL-12:

Interleukin 12

IRSS:

Institut de Recherche en Sciences de la Santé

LMICs:

Low-and middle-income countries

RBP:

Retinol-binding protein

RID:

Retinol isotope dilution

SD:

Standard deviation

TBS:

Total body vitamin A stores

TLR:

Total liver reserves

VA:

Vitamin A

VAD:

Vitamin A deficiency

VIF:

Variance inflation factor

WAZ:

Weight-for-age z-score

WHO:

World Health Organization

WHZ:

Weight-for-height z-score

References

  1. Qi Y, Niu Q, Zhu X, Zhao X, Yang W, Wang X. Relationship between deficiencies in vitamin A and E and occurrence of infectious diseases among children. Eur Rev Med Pharmacol Sci. 2016;20:5009–12.

    PubMed  Google Scholar 

  2. Müller O, Krawinkel M. Malnutrition and health in developing countries. CMAJ. 2005;173:279–86.

    Article  PubMed  PubMed Central  Google Scholar 

  3. WHO. Essential nutrition actions: improving maternal, newborn, infant and young child health and nutrition. Geneva: WHO; 2013.

    Google Scholar 

  4. Larson LM, Guo J, Williams AM, Young MF, Ismaily S, Addo OY, Thurnham D, Tanumihardjo SA, Suchdev PS, Northrop-Clewes CA. Approaches to Assess Vitamin A Status in Settings of Inflammation: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) Project. Nutrients 2018, 10.

  5. Goodman DS. Vitamin A and retinoids in health and disease. N Engl J Med. 1984;310:1023–31.

    Article  CAS  PubMed  Google Scholar 

  6. Almekinder J, Manda W, Soko D, Lan Y, Hoover DR, Semba RD. Evaluation of plasma retinol-binding protein as a surrogate measure for plasma retinol concentrations. Scand J Clin Lab Invest. 2000;60:199–204.

    Article  CAS  PubMed  Google Scholar 

  7. Baumann H, Gauldie J. The acute phase response. Immunol Today. 1994;15:74–80.

    Article  CAS  PubMed  Google Scholar 

  8. Myers MA, Fleck A. Observations on the delay in onset of the acute phase protein response. Br J Exp Pathol. 1988;69:169–76.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Markanday A. Acute phase reactants in infections: Evidence-based review and a guide for clinicians. Open Forum Infect Dis. 2015;2:ofv098.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Rosales FJ, Ritter SJ, Zolfaghari R, Smith JE, Ross AC. Effects of acute inflammation on plasma retinol, retinol-binding protein, and its mRNA in the liver and kidneys of vitamin A-sufficient rats. J Lipid Res. 1996;37:962–71.

    Article  CAS  PubMed  Google Scholar 

  11. Stephensen CB. Vitamin A, infection, and immune function. Annu Rev Nutr. 2001;21:167–92.

    Article  CAS  PubMed  Google Scholar 

  12. Burke RM, Whitehead RD Jr., Figueroa J, Whelan D, Aceituno AM, Rebolledo PA, Revollo R, Leon JS, Suchdev PS. Effects of Inflammation on Biomarkers of Vitamin A Status among a Cohort of Bolivian Infants. Nutrients 2018, 10.

  13. Ingenbleek Y, Van Den Schrieck H-G, De Nayer P, De Visscher M. The role of retinol-binding protein in protein-calorie malnutrition. Metabolism. 1975;24:633–41.

    Article  CAS  PubMed  Google Scholar 

  14. Shankar AH, Genton B, Semba RD, Baisor M, Paino J, Tamja S, Adiguma T, Wu L, Rare L, Tielsch JM. Effect of vitamin A supplementation on morbidity due to plasmodium falciparum in young children in Papua new Guinea: a randomised trial. Lancet. 1999;354:203–9.

    Article  CAS  PubMed  Google Scholar 

  15. Stephensen CB, Gildengorin G. Serum retinol, the acute phase response, and the apparent misclassification of vitamin A status in the third National health and nutrition examination survey. Am J Clin Nutr. 2000;72:1170–8.

    Article  CAS  PubMed  Google Scholar 

  16. Thurnham DI, McCabe GP. Influence of infection and inflammation on biomarkers of nutritional status with an emphasis on vitamin A and iron. Report: Priorities in the assessment of vitamin A and iron status in populations, Panama City, Panama, 15–17 September 2010. World Health Organization. Geneva; 2012.

  17. Thurnham DI, McCabe LD, Haldar S, Wieringa FT, Northrop-Clewes CA, McCabe GP. Adjusting plasma ferritin concentrations to remove the effects of subclinical inflammation in the assessment of iron deficiency: a meta-analysis. Am J Clin Nutr. 2010;92:546–55.

    Article  CAS  PubMed  Google Scholar 

  18. Wessells KR, Hess SY, Ouédraogo ZP, Rouamba N, Ouédraogo J-B, Brown KH. Asymptomatic malaria infection affects the interpretation of biomarkers of iron and vitamin A status, even after adjusting for systemic inflammation, but does not affect plasma zinc concentrations among young children in Burkina Faso. J Nutr. 2014;144:2050–8.

    Article  CAS  PubMed  Google Scholar 

  19. Semba RD, Muhilal, West KP Jr., Natadisastra G, Eisinger W, Lan Y, Sommer A. Hyporetinolemia and acute phase proteins in children with and without xerophthalmia. Am J Clin Nutr. 2000;72:146–53.

    Article  CAS  PubMed  Google Scholar 

  20. Maqsood M, Dancheck B, Gamble MV, Palafox NA, Ricks MO, Briand K, Semba RD. Vitamin A deficiency and inflammatory markers among preschool children in the Republic of the Marshall Islands. Nutr J. 2004;3:21.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nauss KM, Anderson CA, Conner MW, Newberne PM. Ocular infection with herpes simplex virus (HSV-1) in vitamin A-deficient and control rats. J Nutr. 1985;115:1300–15.

    Article  CAS  PubMed  Google Scholar 

  22. Wiedermann U, Tarkowski A, Bremell T, Hanson LA, Kahu H, Dahlgren UI. Vitamin A deficiency predisposes to Staphylococcus aureus infection. Infect Immun. 1996;64:209–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Amimo JO, Michael H, Chepngeno J, Raev SA, Saif LJ, Vlasova AN. Immune impairment associated with vitamin A deficiency: insights from clinical studies and animal model research. Nutrients 2022, 14.

  24. SanJoaquin MA, Molyneux ME. Malaria and vitamin A deficiency in African children: a vicious circle? Malar J. 2009;8:134.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zeba AN, Prével YM, Somé IT, Delisle HF. The positive impact of red palm oil in school meals on vitamin A status: study in Burkina Faso. Nutr J. 2006;5:17.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Tanumihardjo SA, Russell RM, Stephensen CB, Gannon BM, Craft NE, Haskell MJ, Lietz G, Schulze K, Raiten DJ. Biomarkers of nutrition for development (BOND)-Vitamin A review. J Nutr. 2016;146:s1816–48.

    Article  Google Scholar 

  27. District Sanitaire de Dandé. Plan d’action 2016 du district sanitaire de Dandé. Ministère de la Santé, Région des Hauts Bassins, Burkina Faso; 2016.

  28. WHO. WHO Child Growth Standards: Length/height-for age, weight-for-age, weight for length, weight for height - Methods and development. World Health Organization; 2006.

  29. Gannon BM, Sombié OO, Zeba AN, Nama GM, Bekele TH, Woldeyohannes M, van Stuijvenberg ME, Dhansay MA, Urio EM, Kaliwile C. Comparison of total body vitamin A stores using individual versus population 13 C-Natural abundance of serum retinol in preschool children and women residing in 6 diverse African countries. J Nutr. 2023;153:949–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Suri DJ, Sombié OO, Zeba AN, Nama GM, Bekele TH, Woldeyohannes M, van Stuijvenberg ME, Dhansay MA, Urio EM, Loechl CU, et al. Association between biomarkers of inflammation and total liver vitamin A reserves estimated by (13)C-retinol isotope Dilution among preschool children in 5 African countries. J Nutr. 2023;153:622–35.

    Article  PubMed  Google Scholar 

  31. Vitamin A Task force: appropriate uses of vitamin A tracer (stable isotope) methodology. Washington, DC: ILSI Human Nutrition Institute; 2004.

    Google Scholar 

  32. Gibson RS, Ferguson EL. An interactive 24-hour recall for assessing the adequacy of iron and zinc intakes in developing countries. International Food Policy Research Institute (IFPRI) and International Center for Tropical Agriculture (CIAT). Washington, DC; 2008.

    Google Scholar 

  33. Sombié OO, Zeba AN, Somé JW, Kazienga A, Diendere J, Bationo JF, Davis C, Grahn M, Tanumihardjo S, De Henauw S, Abbeddou S. Dietary intake of preformed vitamin A and provitamin A carotenoids are not associated with serum retinol and carotenoid concentrations among children 36–59 months of age in rural Burkina Faso: a cross-sectional study. Eur J Nutr. 2023;62:3311–27.

    Article  PubMed  Google Scholar 

  34. Sombié OO, Abbeddou S, Kazienga A, Valea I, Moulin AM, Zeba AN, Kpoda H, Pietra V, Tinto H. Assessment of the performance of malaria rapid diagnostic test in acutely malnourished children under five years of age in Nanoro-Burkina Faso. J Parasitol Vector Biol. 2020;12:1–6.

    Google Scholar 

  35. Erhardt JG, Estes JE, Pfeiffer CM, Biesalski HK, Craft NE. Combined measurement of ferritin, soluble transferrin receptor, retinol binding protein, and C-reactive protein by an inexpensive, sensitive, and simple sandwich enzyme-linked immunosorbent assay technique. J Nutr. 2004;134:3127–32.

    Article  CAS  PubMed  Google Scholar 

  36. Howe JA, Valentine AR, Hull AK, Tanumihardjo SA. 13C natural abundance in serum retinol acts as a biomarker for increases in dietary provitamin A. Exp Biol Med. 2009;234:140–7.

    Article  CAS  PubMed  Google Scholar 

  37. Gannon B, Kaliwile C, Arscott SA, Schmaelzle S, Chileshe J, Kalungwana N, Mosonda M, Pixley K, Masi C, Tanumihardjo SA. Biofortified orange maize is as efficacious as a vitamin A supplement in Zambian children even in the presence of high liver reserves of vitamin A: a community-based, randomized placebo-controlled trial. Am J Clin Nutr. 2014;100:1541–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Gannon BM, Tanumihardjo SA. Comparisons among equations used for retinol isotope Dilution in the assessment of total body stores and total liver reserves. J Nutr. 2015;145:847–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Tanumihardjo SA. Vitamin A: biomarkers of nutrition for development. Am J Clin Nutr. 2011;94:s658–65.

    Article  Google Scholar 

  40. Kennedy G, Ballard T, Dop MC. Guidelines for measuring household and individual dietary diversity. Food and Agriculture Organization; 2011.

  41. WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. World Health Organization; 2011.

  42. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21:459–68.

    Article  PubMed  Google Scholar 

  43. Zeba AN, Bationo JF, Sombié OO, Diendéré J. Vitamin A deficiency among rural primary school children, a still neglected group for vitamin A supplementation strategies. J Nutr Food Secur. 2021;6:246–54.

    Google Scholar 

  44. Bationo J, Zeba A, Abbeddou S, Coulibaly N, Sombier O, Sheftel J, Bassole I, Barro N, Ouedraogo J, Tanumihardjo S. Serum carotenoids reveal poor fruit and vegetable intake among schoolchildren in Burkina Faso. Nutrients. 2018;10:1422.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Sombié OO, Zeba AN, Somé JW, Kazienga A, Grahn M, Tanumihardjo SA, De Henauw S, Abbeddou S. A comparative study on indicators of vitamin A status and risk factors for sensitivity and specificity of the methods to detect vitamin A deficiency. Nutr Metab. 2023;20:49.

    Article  PubMed  Google Scholar 

  46. Mason JB, Lotfi M, Dalmiya N, Sethuraman K, Deitchler M, Geibel S, Gillenwater K, Gilman A, Mason K, Mock N. The micronutrient report: current progress and trends in the control of vitamin A, iodine, and iron deficiencies. Ottawa: World Micronutrient Initiative; 2001.

    Google Scholar 

  47. Olson JA. Serum levels of vitamin A and carotenoids as reflectors of nutritional status. J Natl Cancer Inst. 1984;73:1439–44.

    CAS  PubMed  Google Scholar 

  48. Van Stuijvenberg ME, Dhansay MA, Nel J, Suri D, Grahn M, Davis CR, Tanumihardjo SA. South African preschool children habitually consuming sheep liver and exposed to vitamin A supplementation and fortification have hypervitaminotic A liver stores: a cohort study. Am J Clin Nutr. 2019;110:91–101.

    Article  PubMed  Google Scholar 

  49. Direction de la Nutrition. Plan de renforcement de la lutte contre les carences en micronutriment 2015–2020. Ministere de la Santé du Burkina Faso, Ouagadougou; 2015.

  50. Lompo P, Tahita MC, Sorgho H, Kaboré W, Kazienga A, Nana ACB, Natama HM, Bonkoungou IJO, Barro N, Tinto H. Pathogens associated with acute diarrhea, and comorbidity with malaria among children under five years old in rural Burkina Faso. Pan Afr Med J 2021, 38.

  51. Sivakumar B, Reddy V. Absorption of labelled vitamin A in children during infection. Br J Nutr. 1972;27:299–304.

    Article  CAS  PubMed  Google Scholar 

  52. Rubin LP, Ross AC, Stephensen CB, Bohn T, Tanumihardjo SA. Metabolic effects of inflammation on vitamin A and carotenoids in humans and animal models. Adv Nutr. 2017;8:197–212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Shetty PS. Nutrition, immunity and infection. CABI; 2010.

  54. Tanumihardjo SA, Permaesih D, Muherdiyantiningsih, Rustan E, Rusmil K, Fatah AC, Wilbur S, Muhilal, Karyadi D, Olson JA. Vitamin A status of Indonesian children infected with Ascaris lumbricoides after dosing with vitamin A supplements and albendazole. J Nutr. 1996;126:451–7.

    Article  CAS  PubMed  Google Scholar 

  55. Zijlstra RT, Donovan SM, Odle J, Gelberg HB, Petschow BW, Gaskins HR. Protein-energy malnutrition delays small-intestinal recovery in neonatal pigs infected with rotavirus. J Nutr. 1997;127:1118–27.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Authors are very grateful to the participants in the Sourkoudougou and Banakeledaga villages, and the staff of the Centre de Santé et de Promotion Sociale. Our appreciation goes to the health officials for facilitating the implementation of the study. We would like to thank our data collectors for their support.

Funding

Field activities and sample analysis were supported by the International Atomic Energy Agency (IAEA, Vienna) through a Regional African Coordinated Research project on “the use of stable isotope techniques to monitor and assess VA status of children susceptible to infection”. The findings and conclusions in this report are those of the authors and do not necessarily reflect IAEA positions or policies. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Centre National de Recherche Scientifique et Technologique, Institut de Recherche en Sciences de la Santé/Direction Régionale de l’Ouest, Unité Nutrition et Maladies Métaboliques, Bobo– Dioulasso, Burkina Faso

    Olivier O. Sombié & Augustin N. Zeba

  2. Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium

    Olivier O. Sombié, Stefaan De Henauw & Souheila Abbeddou

  3. Centre National de Recherche Scientifique et Technologique, Institut de Recherche en Sciences de la Santé, Unité Nutrition et Maladies Métaboliques, Ouagadougou, Burkina Faso

    Jérome W. Somé

  4. Department of Translational Physiology, Infectiology and Public Health, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium

    Adama Kazienga

  5. African Union Development Agency, New Partnership for Africa’s development, Midrand, South Africa

    Jean F. Bationo

  6. Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, US

    Christopher Davis & Sherry A. Tanumihardjo

Authors
  1. Olivier O. Sombié
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Augustin N. Zeba
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Jérome W. Somé
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Adama Kazienga
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Jean F. Bationo
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Christopher Davis
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Sherry A. Tanumihardjo
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Stefaan De Henauw
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Souheila Abbeddou
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

ANZ, OOS and ST were responsible for the design of the study. OOS, JFB, CD and MG conducted the research. ANZ, JWS, ST, SDH and SA supervised data collection. OOS, AK and SA completed the statistical analyses and OOS drafted the manuscript. SA and JWS contributed to the writing of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Olivier O. Sombié.

Ethics declarations

Ethical consideration

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Institutional Review Boards of the Institut de Recherche en Sciences de la Santé (IRSS, Bobo-Dioulasso) and the Hauts-Bassins Health Department, respectively, under the reference numbers N/Ref A11- 2016/CEIRES and N°2016- EE0202/MS/RHBS/DRS. Before enrolling the child in the study, caregivers provided written informed consents for participation of their child in the study and for collection of biological samples. Children who tested positive for malaria using blood smear were treated with a combination of artemether and lumefantrine over 3 days. Children who were diagnosed with intestinal parasites were treated with 400 mg albendazole per day, for 3 days. Children with moderate or mild anemia were referred to an outpatient facility at the health center of Sourkoudougou.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sombié, O.O., Zeba, A.N., Somé, J.W. et al. Association between vitamin A status, inflammations, and infections in children 36–59 months of age in rural Burkina Faso: A cross - sectional study. J Health Popul Nutr 44, 107 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41043-025-00840-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41043-025-00840-3

Keywords

Journal of Health, Population and Nutrition

ISSN: 2072-1315

Contact us