Iron status of Kenyan pregnant women after adjusting for inflammation using brinda regression analysis and other correction methods

Serum ferritin concentration is the preferred biomarker to assess population iron status in the absence of inflammation. Interpretation of this biomarker is complicated in populations with a high burden of infection, however, because inflammation increases serum ferritin concentration independently of iron status. We aimed to compare estimates of iron status of Kenyan pregnant women, with circulating ferritin concentrations adjusted for inflammation using newly proposed methods by the BRINDA project, or using previously proposed adjustment methods. We re-analyzed data from pregnant Kenyan women living in a rural area where malaria is highly endemic (n = 470) or in an urban area (n = 402). As proposed by the BRINDA group, we adjusted individual ferritin concentration by internal regression for circulating concentrations of C-reactive protein (CRP) and α 1 -acid glycoprotein (AGP). Other adjustment methods comprised: (a) arithmetic correction factors based on CRP or AGP; (b) exclusion of subjects with inflammation (CRP >5 mg/L or AGP >1 g/L); and (c) higher ferritin cut-off value (<30 µg/L). We additionally adjusted for Plasmodium infection as appropriate. Lastly, we assessed iron status without adjustment for inflammation. All correction methods increased prevalence of iron deficiency compared to the unadjusted estimates. This increase was more pronounced with the internal regression correction method. The iron deficiency prevalence estimate increased from 53% to 87% in rural Kisumu study and from 30% to 41% in the urban Nairobi study after adjusting for inflammation (CRP and AGP) using the BRINDA internal regression method. When we corrected for both inflammation and Plasmodium infection using the regression correction, it resulted in lower prevalence estimates compared to uninfected women. Application of linear regression methods to adjust circulating ferritin concentration for inflammation leads to markedly decreased point estimates for ferritin concentration and increased estimates for the prevalence of iron deficiency in pregnancy. Study design and population: We used data from studies that were conducted from 2011 to 2014 in two distinct regions in Kenya—a rural area (Kisumu County, Kisumu, Kenya; henceforth referred to as the Kisumu data), and an urban area (Nairobi County, Nairobi, Kenya; henceforth referred to as the Nairobi data). Plasmodium infection is highly endemic in the Kisumu study area but is uncommon in Nairobi study area due to its high altitude (around 1,650–1,800 m above sea level). In Nairobi, Plasmodium infection is mostly imported from other regions. The main results of these studies have been published elsewhere [8,9]. Rural area (Kisumu) data: The prenatal iron and malaria (PIMAL) study concerned a randomized placebo-controlled trial to measure the effect of antenatal iron supplementation on maternal Plasmodium infection risk, and maternal and neonatal outcomes at delivery and one-month post-partum. For the current study, we used data from samples collected at baseline. The study was conducted in the administrative areas of Ojolla, Kanyawegi, Osiri, and Rota Sub-Locations, Kisumu County, Kisumu, Kenya. Pregnant women were recruited when aged 15–45 years, with singleton pregnancies, gestational age 13–23 weeks (determined by obstetric ultrasonography), and hemoglobin concentration >90 g/L. Venous blood samples were collected in EDTA tubes. Plasma concentrations of ferritin, soluble transferrin receptor, transferrin, CRP, and AGP were assessed on a Beckman Coulter Unicel DxC 880i analyzer at Meander Medical Centre, Amersfoort, The Netherlands [9]. For CRP, data below the assay limit of detection (LOD) of 1 mg/L were censored and reported by the laboratory as imputed values at LOD/2 (i.e., 0.5 mg/L). Plasmodium infection was indicated by the presence in plasma of Plasmodium antigens (histidine-rich protein-2, which is specific for P. falciparum; or lactate dehydrogenase specific to either P. falciparum or to non-falciparum human Plasmodium species; Access Bio rapid dipstick test), or the presence in erythrocytes of P. falciparum-specific DNA, as determined by quantitative polymerase chain reaction. Urban area (Nairobi) data: The MNS 2014 study concerned a survey to assess micronutrient status, nutritional knowledge, and dietary patterns among pregnant women in their second trimester of pregnancy who attended antenatal clinics at Aga Khan Hospital, St. Mary’s Hospital, and Mama Lucy hospital in Nairobi County, Kenya [8]. The three hospitals were purposely chosen to represent urban women from high, medium, and low socio-economic status, respectively. The subjects recruited were sampled consecutively and proportionately to the daily turnover of women in their second pregnancy trimester for each of these three facilities, until the sample size for each facility was attained. Experienced research staff were trained on study-specific procedures of data collection, specimen handling, and analysis. Venous blood was collected in EDTA tubes. Plasmodium infection tests were done on site using rapid diagnostic tests specific for P. falciparum (histidine-rich protein 2). Serum concentrations of ferritin, soluble transferrin receptor, CRP, and AGP were measured by a multiplex enzyme immunoassay sandwich method with fluorescence detection [10]. No limit of detection was reported for CRP. Sample size requirements were calculated for the original purposes of each study and not reported because they are irrelevant to the present article. The PIMAL study was approved by independent ethics committees from London School of Hygiene and Tropical Medicine, UK, and the Kenyatta National Hospital/University of Nairobi, Kenya. It was registered at Clinicaltrials.gov (identifier: {“type”:”clinical-trial”,”attrs”:{“text”:”NCT 01308112″,”term_id”:”NCT01308112″}}NCT 01308112). For re-analysis of the Kisumu data for the current article, the authors obtained additional approval from the Kenyatta National Hospital/University of Nairobi Ethical Review Board. The MNS 2014 study was approved by the Kenya Medical Research Institute Scientific and Ethics Review Unit (KEMRI/CPHR/SERU/2769—www.kemri.org) and the Aga Khan University Research Ethics Committee (2014/REC-53). Written informed consent was obtained from all study subjects in both studies. The following data, collected in the second pregnancy trimester, were used for this article: Kisumu 2011–2013 data and Nairobi 2014 data. Statistical Package for Social Sciences (SPSS) software version 22 and SAS 9.4 software (SAS Institute, Cary, NC, USA) were used for data analysis. As per recommendations by the BRINDA group, we used the Internal Regression Correction (IRC) approach (10) to adjust for inflammation using CRP and AGP. The IRC approach uses linear regression to adjust a biomarker by the concentration of CRP or AGP on a continuous scale and Plasmodium infection as a dichotomous variable. Ferritin concentration was log-transformed to normalize its distribution and to stabilize its variance, and concentrations of CRP and AGP concentrations were log-transformed under the assumption that this would linearize their relationship with the log-transformed ferritin concentration. Thus, the following regression equation was applied to adjust individual ferritin concentrations: where the subscripts adj and unadj refer to adjusted and unadjusted ferritin concentrations, β1, β2, and β3 are the regression coefficients for CRP, AGP, and Plasmodium infection, respectively, and the subscript ref refers to reference values that are recommended under the assumption that ferritin concentrations increase only when these inflammatory markers exceed this threshold value [5,11]. For CRP, internal reference values employed were 0.5 mg/L and 1.0 mg/L for Kisumu and Nairobi, respectively. For AGP, internal reference values utilized were 0.5 g/L and 0.3 g/L for Kisumu and Nairobi, respectively. A test of multicollinearity between log-transformed CRP and AGP (ln-CRP and ln-AGP) was assessed on the basis of a test of tolerance (>0.1) to determine whether it was appropriate to include all variables in the model. Because the BRINDA group did not report estimates for the regression coefficients for their meta-regression of data from pregnant women, we estimated these coefficients separately for the Kisumu and the Nairobi studies. Estimates for the regression coefficients were exponentiated to express associations in the original units of measurements. Iron deficiency was determined by applying a cut-off of <15 μg/L [2] to inflammation-corrected ferritin concentrations. As per BRINDA recommendations, the lowest deciles of CRP and AGP were set as internal reference values to avoid over-adjustment for low levels of inflammation, and adjustments were restricted to ferritin concentrations that corresponded to the CRP or AGP exceeding their lowest decile. Specific internal reference values were obtained for each of the groups described above. This was done on the basis of all values for CRP and AGP, as was suggested by the BRINDA group. We considered, however, that regression over censored independent variables is likely to result in biased estimators for the regression coefficients. For this reason, we also conducted an analysis of the Kisumu dataset with exclusion of observations with CRP values below the LOD. Although this truncation leads to a reduced sample size, and thus to a loss of efficiency, it has the advantages that the method is simple and that regression coefficients will be consistent, i.e., with increasing sample size, the estimates will tend towards the true value [12]. The categorical Correction Factor (CF) approach, as proposed by Thurnham et al. [6], uses arithmetic CFs that are derived from the following 4-group inflammation-adjustment model: (1) reference (CRP concentration ≤5 mg/L and AGP concentration ≤1 g/L); (2) incubation (CRP concentration >5 mg/L and AGP concentration ≤1 g/L); (3) early convalescence (CRP concentration >5 mg/L and AGP concentration >1 g/L); and (4) late convalescence (CRP concentration ≤5 mg/L and concentration AGP >1 g/L). In addition, CFs were derived by grouping those with inflammation or Plasmodium infection into 2 groups, in which CRP, AGP, or Plasmodium infection were used independently of each other. Internal Correction Factors (ICFs) were then generated by dividing geometric mean (GM) ferritin values of the non-inflammation group by GM ferritin values of each inflammation group: where ref and inflam denote the reference group and the inflammation group, respectively. Subsequently, raw ferritin values in individuals in the groups with raised inflammatory markers were multiplied by the ICFs matching their respective inflammation group to arrive at adjusted ferritin values. In line with the IRC approach, ICFs were calculated for each of the groups described above. To compare ferritin concentrations between Kisumu and Nairobi, after excluding cases with inflammation, a t-test was utilized to test the log-normal ratio of the geometric means and obtain corresponding 95% CIs. In the “exclusion” approach, individuals with inflammation (as defined by a CRP concentration >5 mg/L or AGP concentration >1 g/L, or both) or with Plasmodium infection were excluded from the analysis. The estimated prevalence of iron deficiency was then calculated among those remaining. The method used to calculate 95% CIs of prevalence estimates was Wilson’s score interval. For the increased ferritin concentration approach, we defined iron deficiency as ferritin concentrations <15 μg/L or <30 μg/L in individuals without or with inflammation (CRP concentration >5 mg/L or AGP concentration >1 g/L, or both), respectively. Wilson’s score interval was used to calculate corresponding 95% CIs. Lastly, we reported unadjusted prevalence estimates for iron deficiency. Again, 95% CIs were obtained with Wilson’s score interval.