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The objective of this study was to determine and compare anemia and iron-deficiency anemia (IDA) rates in young Kenyan children who are HIV infected (HI), HIV exposed, uninfected (HEU), and HIV unexposed (HU). Questionnaires, anthropometrics, and blood samples were collected from HI, HEU, and HU aged 18 to 36 months. Descriptive statistics, Fisher’s exact tests, and linear regression were used for analysis. Of 137 total participants, HI (n = 18), HEU (n = 70), and HU (n = 49), 61.1%, 53.6%, and 36.7%, respectively, were anemic, with mean hemoglobin levels highest in HU (P =.006). After adjusting for covariates, HI (β = −9.6, 95% CI:−17.3 to −2.0) and HEU (β = −7.4, 95% CI: −12.9 to −1.9) had lower hemoglobin levels compared with HU. The proportion of children with IDA did not differ significantly across groups (P =.08). HEU have rates of anemia and IDA similar to HI. Anemia risk is generally higher in HEU than HU, even after adjusting for covariates.
Study design and population: This was a descriptive cross-sectional analysis nested within a larger study assessing neurodevelopment among young children in Kenya (NeuroDEV) as part of the Academic Model Providing Access to Healthcare (AMPATH) consortium. The AMPATH HIV care program, born from a 20-year partnership between Indiana University School of Medicine, Moi University School of Medicine, and the Moi Teaching and Referral Hospital (MTRH) in Eldoret, Kenya, has enrolled over 160 000 patients and currently provides care for approximately 15 000 children who are HIV-positive and HIV-exposed in 65 clinics in western Kenya.16,17 The children and their caregivers were recruited for the NeuroDEV study from the MTRH and AMPATH Module 4 pediatric clinics between 12/2017 and 9/2019. Children who were HI were recruited from the AMPATH pediatric HIV outpatient clinic located in MTRH. Children who were HEU or HU were recruited from the MTRH well-baby clinic. Eligible children were 18 to 36 months of age at the time of enrolment. A sample of blood was taken at enrolment to evaluate blood indices and SF as biological factors that could affect development (results reported elsewhere18). Each child’s caregiver participated in a standardized interview to collect demographic information and medical history, including birth history and HIV status (mother’s and child’s). The caregiver also provided information on household wealth and possessions, maternal education, water/sanitation, and income using the Wealth-Assets-Maternal Education-Income (WAMI index19). Each child’s body mass and standing height was measured. Three 4 mL blood samples were collected from each child using EDTA vacutainer tubes (Becton Dickinson, San Jose, CA, USA). The first tube was collected for a CBC, conducted using the Coulter ACT 5diff analyzer (Beckman Coulter, France). Output measurements included white blood cell count, hemoglobin concentration (Hgb), hematocrit, MCV, mean cell hemoglobin, mean cell hemoglobin concentration, red cell distribution width, and platelet count. Blood from the second tube was used to assess SF levels using the COBAS INTEGRA 400 plus analyzer (Roche Diagnostics, Switzerland). Because some children were resistant to the blood drawing procedure, insufficient blood volumes were obtained to complete all labs in some children. As such, SF results were not as complete as CBC results. Because laboratory assays were performed in the United States long after sample collection, the results of the blood tests were not communicated back to medical personnel in Kenya or participants. Study data were collected and managed using REDCap electronic data capture tools hosted at Indiana University.20 WHO guidelines classify a child aged 6 to 59 months as anemic if their hemoglobin falls below 110 g/L.21 However, because children attending clinics in and near Eldoret live at altitudes over 2000 m above sea level, we classified a child as having anemia if their hemoglobin concentration measured less than 118 g/L, based on a WHO-published algorithm.21 Those with anemia were further classified as having mild (108-118 g/L), moderate (78-108 g/L), or severe (<78 g/L) disease.17 Sensitivity analyses using the 110 g/L cut-off were also conducted. Iron deficiency may be diagnosed with several models, including levels of serum ferritin (SF), levels of soluble transferrin receptor, and multiple-criteria indicators including the soluble transferrin receptor/ferritin index.5,22,23 However, each of these requires additional studies beyond the standard complete blood count (CBC), and in many low-resource settings, these studies are either unavailable or prohibitively expensive. For this study, children with SF concentrations below 12 μg/L were considered to have ferritin deficiency, and, when coupled with the threshold for anemia, were categorized as IDA. For the analysis comparing sensitivity and specificity of MCV in detecting IDA, children with MCV below 72 fL were considered to have low MCV, which was then coupled with the threshold for anemia to qualify as IDA. Data were analyzed using R 4.0.0 (www.r-project.org). For all analyses, results were considered statistically significant if P < .05. Data related to socioeconomic status (water, sanitation, income, maternal education, and possessions) were summarized individually and in the WAMI index, a composite measure of socioeconomic status.19 Body mass and standing height were converted to Z-scores based on the child’s age and mass-to-height ratio using growth charts created from the WHO Multicentre Growth Reference Study.24 Comparisons across groups were made using analysis of variance (ANOVA) for continuous variables, the Kruskal-Wallis rank-sum test for skewed continuous and ordinal variables, and Fisher’s exact test for categorical variables. Laboratory variables were treated as continuous and summarized by their means and standard deviations, except for SF, which exhibited significant positive skew and was summarized using its median and interquartile range. Differences in distribution across all groups were assessed using ANOVA; differences between 2 groups were assessed using a two-sample t-test. To better understand the relationship between HIV status and hemoglobin concentrations, linear regression models adjusting for age, sex, anthropometric measurements, WAMI, and socioeconomic variables contributing to WAMI were evaluated. Hemoglobin concentration was used to define anemia as a binary (anemia/no anemia) and categorical (none/mild/moderate/severe) variable. HIV status was evaluated as a risk factor for lower hemoglobin concentrations using multivariate linear regression. WAMI, components of WAMI, the child’s age, anthropometric measurements, and gender were also evaluated as potential effect modifiers. Fisher’s exact test was used to identify differences in the frequency of low MCV and ferritin deficiency by HIV exposure group. Among children who were anemic, the sensitivity and specificity of low MCV as a surrogate for ferritin deficiency was evaluated. All caregivers provided written informed consent for their child’s participation in this study, and the study was approved by institutional review boards at Indiana University School of Medicine in Indianapolis, USA (1601531540) and Moi University (IREC/2016/09) in Eldoret, Kenya.
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